[Docs] Translate model_zoo.md (#556)
* translate model_zoo.md * fix lint * update maskfeat link * Update docs/zh_cn/model_zoo.md Co-authored-by: Songyang Zhang <tonysy@users.noreply.github.com> * Update docs/zh_cn/model_zoo.md Co-authored-by: Songyang Zhang <tonysy@users.noreply.github.com> * Update docs/zh_cn/model_zoo.md Co-authored-by: Songyang Zhang <tonysy@users.noreply.github.com> Co-authored-by: Songyang Zhang <tonysy@users.noreply.github.com>pull/582/head
Yixiao Fang
parent
27374e1f0d
commit
35cb9b81cd
|
|
@ -1,80 +1,397 @@
|
|||
# Model Zoo
|
||||
# 模型库
|
||||
|
||||
All models and part of benchmark results are recorded below.
|
||||
本部分内容主要介绍 MMSelfSup 支持的模型和部分下游任务的评测结果。
|
||||
|
||||
- [Model Zoo](#model-zoo)
|
||||
- [Statistics](#statistics)
|
||||
- [Benchmarks](#benchmarks)
|
||||
- [ImageNet Linear Evaluation](#imagenet-linear-evaluation)
|
||||
- [ImageNet Fine-tuning](#imagenet-fine-tuning)
|
||||
- [模型库](#模型库)
|
||||
- [数据统计](#数据统计)
|
||||
- [下游任务评测](#下游任务评测)
|
||||
- [ImageNet](#imagenet)
|
||||
|
||||
## Statistics
|
||||
## 数据统计
|
||||
|
||||
- Number of papers: 17
|
||||
- 论文数量: 18
|
||||
|
||||
- Number of checkpoints: xx ckpts
|
||||
- 模型文件数量: 62
|
||||
|
||||
| Algorithm | Config | Download |
|
||||
| ------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| [Relative Location](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/README.md) | [relative-loc_resnet50_8xb64-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k_20220225-84784688.pth) \| [log](https://download.openmmlab.com/mmselfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k_20220211_124808.log.json) |
|
||||
| [Rotation Prediction](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/README.md) | [rotation-pred_resnet50_8xb16-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k_20220225-5b9f06a0.pth) \| [log](https://download.openmmlab.com/mmselfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k_20220215_185303.log.json) |
|
||||
| [DeepCluster](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/deepcluster/README.md) | [deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/deepcluster/deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/deepcluster/deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k-bb8681e2.pth) |
|
||||
| [NPID](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/npid/README.md) | [npid_resnet50_8xb32-steplr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/npid/npid_resnet50_8xb32-steplr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/npid/npid_resnet50_8xb32-steplr-200e_in1k_20220225-5fbbda2a.pth) \| [log](https://download.openmmlab.com/mmselfsup/npid/npid_resnet50_8xb32-steplr-200e_in1k_20220215_185513.log.json) |
|
||||
| [ODC](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/odc/README.md) | [odc_resnet50_8xb64-steplr-440e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/odc/odc_resnet50_8xb64-steplr-440e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/odc/odc_resnet50_8xb64-steplr-440e_in1k_20220225-a755d9c0.pth) \| [log](https://download.openmmlab.com/mmselfsup/odc/odc_resnet50_8xb64-steplr-440e_in1k_20220215_235245.log.json) |
|
||||
| [SimCLR](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simclr/README.md) | [simclr_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simclr/simclr_resnet50_8xb32-coslr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/simclr/simclr_resnet50_8xb32-coslr-200e_in1k_20220428-46ef6bb9.pth) \| [log](https://download.openmmlab.com/mmselfsup/simclr/simclr_resnet50_8xb32-coslr-200e_in1k_20220411_182427.log.json) |
|
||||
| | [simclr_resnet50_16xb256-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simclr/simclr_resnet50_16xb256-coslr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/simclr/simclr_resnet50_16xb256-coslr-200e_in1k_20220428-8c24b063.pth) \| [log](https://download.openmmlab.com/mmselfsup/simclr/simclr_resnet50_16xb256-coslr-200e_in1k_20220423_205520.log.json) |
|
||||
| [MoCo v2](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mocov2/README.md) | [mocov2_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/moco/mocov2_resnet50_8xb32-coslr-200e_in1k_20220225-89e03af4.pth) \| [log](https://download.openmmlab.com/mmselfsup/moco/mocov2_resnet50_8xb32-coslr-200e_in1k_20220210_110905.log.json) |
|
||||
| [BYOL](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/README.md) | [byol_resnet50_8xb32-accum16-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_8xb32-accum16-coslr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/byol/byol_resnet50_8xb32-accum16-coslr-200e_in1k_20220225-5c8b2c2e.pth) \| [log](https://download.openmmlab.com/mmselfsup/byol/byol_resnet50_8xb32-accum16-coslr-200e_in1k_20220214_115709.log.json) |
|
||||
| | [byol_resnet50_16xb256-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_16xb256-coslr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/byol/byol_resnet50_16xb256-coslr-200e_in1k_20220527-b6f8eedd.pth) \| [log](https://download.openmmlab.com/mmselfsup/byol/byol_resnet50_16xb256-coslr-200e_in1k_20220509_213052.log.json) |
|
||||
| | [byol_resnet50_8xb32-accum16-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_8xb32-accum16-coslr-300e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/byol/byol_resnet50_8xb32-accum16-coslr-300e_in1k_20220225-a0daa54a.pth) \| [log](https://download.openmmlab.com/mmselfsup/byol/byol_resnet50_8xb32-accum16-coslr-300e_in1k_20220210_095852.log.json) |
|
||||
| [SwAV](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/swav/README.md) | [swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96.py) | [model](https://download.openmmlab.com/mmselfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96_20220225-0497dd5d.pth) \| [log](https://download.openmmlab.com/mmselfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96_20220211_061131.log.json) |
|
||||
| [DenseCL](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/densecl/README.md) | [densecl_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/densecl/densecl_resnet50_8xb32-coslr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/densecl/densecl_resnet50_8xb32-coslr-200e_in1k_20220225-8c7808fe.pth) \| [log](https://download.openmmlab.com/mmselfsup/densecl/densecl_resnet50_8xb32-coslr-200e_in1k_20220215_041207.log.json) |
|
||||
| [SimSiam](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simsiam/README.md) | [simsiam_resnet50_8xb32-coslr-100e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k_20220225-68a88ad8.pth) \| [log](https://download.openmmlab.com/mmselfsup/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k_20220210_195405.log.json) |
|
||||
| | [simsiam_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k_20220225-2f488143.pth) \| [log](https://download.openmmlab.com/mmselfsup/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k_20220210_195402.log.json) |
|
||||
| [BarlowTwins](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/barlowtwins/README.md) | [barlowtwins_resnet50_8xb256-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k_20220419-5ae15f89.pth) \| [log](https://download.openmmlab.com/mmselfsup/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k_20220413_111555.log.json) |
|
||||
| [MoCo v3](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mocov3/README.md) | [mocov3_vit-small-p16_32xb128-fp16-coslr-300e_in1k-224](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mocov3/mocov3_vit-small-p16_32xb128-fp16-coslr-300e_in1k-224.py) | [model](https://download.openmmlab.com/mmselfsup/moco/mocov3_vit-small-p16_32xb128-fp16-coslr-300e_in1k-224_20220225-e31238dd.pth) \| [log](https://download.openmmlab.com/mmselfsup/moco/mocov3_vit-small-p16_32xb128-fp16-coslr-300e_in1k-224_20220222_160222.log.json) |
|
||||
| [MAE](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mae/README.md) | [mae_vit-base-p16_8xb512-coslr-400e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mae/mae_vit-base-p16_8xb512-coslr-400e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/mae/mae_vit-base-p16_8xb512-coslr-400e_in1k-224_20220223-85be947b.pth) \| [log](https://download.openmmlab.com/mmselfsup/mae/mae_vit-base-p16_8xb512-coslr-300e_in1k-224_20220210_140925.log.json) |
|
||||
| [SimMIM](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simmim/README.md) | [simmim_swin-base_16xb128-coslr-100e_in1k-192](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192.py) | [model](https://download.openmmlab.com/mmselfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192_20220316-1d090125.pth) \| [log](https://download.openmmlab.com/mmselfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192_20220316-1d090125.log.json) |
|
||||
| [CAE](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simmim/README.md) | [cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/cae/cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/cae/cae_vit-base-p16_16xb256-coslr-300e_in1k-224_20220427-4c786349.pth) \| [log](https://download.openmmlab.com/mmselfsup/cae/cae_vit-base-p16_16xb256-coslr-300e_in1k-224_20220427-4c786349.log.json) |
|
||||
## 下游任务评测
|
||||
|
||||
Remarks:
|
||||
### ImageNet
|
||||
|
||||
- The training details are recorded in the config names.
|
||||
ImageNet 有多个版本，不过最常用的是 ILSVRC 2012。我们提供了基于各类算法的预训练模型的分类结果，包括线性评估和微调，同时有对应的模型和日志文件。
|
||||
|
||||
- You can click algorithm name to obtain more information.
|
||||
|
||||
## Benchmarks
|
||||
|
||||
In the following tables, we only display ImageNet linear evaluation, ImageNet fine-tuning, COCO17 object detection and instance segmentation, and PASCAL VOC12 Aug semantic segmentation. You can click algorithm name above to check more comprehensive benchmark results.
|
||||
|
||||
### ImageNet Linear Evaluation
|
||||
|
||||
If not specified, we use linear evaluation setting from [MoCo](http://openaccess.thecvf.com/content_CVPR_2020/papers/He_Momentum_Contrast_for_Unsupervised_Visual_Representation_Learning_CVPR_2020_paper.pdf) as default. Other settings are mentioned in Remarks.
|
||||
|
||||
| Algorithm | Config | Remarks | Top-1 (%) |
|
||||
| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- | --------- |
|
||||
| Relative Location | [relative-loc_resnet50_8xb64-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py) | | 38.78 |
|
||||
| Rotation Prediction | [rotation-pred_resnet50_8xb16-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py) | | 48.12 |
|
||||
| DeepCluster | [deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k.py](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/deepcluster/deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k.py) | | 46.92 |
|
||||
| NPID | [npid_resnet50_8xb32-steplr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/npid/npid_resnet50_8xb32-steplr-200e_in1k.py) | | 58.97 |
|
||||
| ODC | [odc_resnet50_8xb64-steplr-440e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/odc/odc_resnet50_8xb64-steplr-440e_in1k.py) | | 53.43 |
|
||||
| SimCLR | [simclr_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simclr/simclr_resnet50_8xb32-coslr-200e_in1k.py) | SimSiam paper setting | 62.56 |
|
||||
| | [simclr_resnet50_16xb256-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simclr/simclr_resnet50_16xb256-coslr-200e_in1k.py) | SimSiam paper setting | 66.66 |
|
||||
| MoCo v2 | [mocov2_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k.py) | | 67.58 |
|
||||
| BYOL | [byol_resnet50_8xb32-accum16-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_8xb32-accum16-coslr-200e_in1k.py) | SimSiam paper setting | 71.72 |
|
||||
| | [byol_resnet50_16xb256-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_16xb256-coslr-200e_in1k.py) | SimSiam paper setting | 71.88 |
|
||||
| | [byol_resnet50_8xb32-accum16-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_8xb32-accum16-coslr-300e_in1k.py) | SimSiam paper setting | 72.93 |
|
||||
| SwAV | [swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96.py) | SwAV paper setting | 70.47 |
|
||||
| DenseCL | [densecl_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/densecl/densecl_resnet50_8xb32-coslr-200e_in1k.py) | | 63.62 |
|
||||
| SimSiam | [simsiam_resnet50_8xb32-coslr-100e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k.py) | SimSiam paper setting | 68.28 |
|
||||
| | [simsiam_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k.py) | SimSiam paper setting | 69.84 |
|
||||
| Barlow Twins | [barlowtwins_resnet50_8xb256-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k.py) | Barlow Twins paper setting | 71.66 |
|
||||
| MoCo v3 | [mocov3_vit-small-p16_32xb128-fp16-coslr-300e_in1k-224](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mocov3/mocov3_vit-small-p16_32xb128-fp16-coslr-300e_in1k-224.py) | MoCo v3 paper setting | 73.19 |
|
||||
|
||||
### ImageNet Fine-tuning
|
||||
|
||||
| Algorithm | Config | Remarks | Top-1 (%) |
|
||||
| --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------- | --------- |
|
||||
| MAE | [mae_vit-base-p16_8xb512-coslr-400e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mae/mae_vit-base-p16_8xb512-coslr-400e_in1k.py) | | 83.1 |
|
||||
| SimMIM | [simmim_swin-base_16xb128-coslr-100e_in1k-192](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192.py) | | 82.9 |
|
||||
| CAE | [cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/cae/cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k.py) | | 83.2 |
|
||||
<table class="docutils">
|
||||
<thead>
|
||||
<tr>
|
||||
<th rowspan="2">算法</th>
|
||||
<th rowspan="2">主干</th>
|
||||
<th rowspan="2">预训练 Epoch</th>
|
||||
<th rowspan="2">Batch 大小</th>
|
||||
<th colspan="2" align="center">结果 (Top-1 %)</th>
|
||||
<th colspan="3" align="center">链接</th>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>线性评估</th>
|
||||
<th>微调</th>
|
||||
<th>预训练</th>
|
||||
<th>线性评估</th>
|
||||
<th>微调</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<td>Relative-Loc</td>
|
||||
<td>ResNet50</td>
|
||||
<td>70</td>
|
||||
<td>512</td>
|
||||
<td>40.4</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k/relative-loc_resnet50_8xb64-steplr-70e_in1k_20220825-daae1b41.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k/relative-loc_resnet50_8xb64-steplr-70e_in1k_20220802_223045.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-c2a0b188.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220804_194226.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>Rotation-Pred</td>
|
||||
<td>ResNet50</td>
|
||||
<td>70</td>
|
||||
<td>128</td>
|
||||
<td>47.0</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k/rotation-pred_resnet50_8xb16-steplr-70e_in1k_20220825-a8bf5f69.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k/rotation-pred_resnet50_8xb16-steplr-70e_in1k_20220805_113136.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-7c6edcb3.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220808_143921.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>NPID</td>
|
||||
<td>ResNet50</td>
|
||||
<td>200</td>
|
||||
<td>256</td>
|
||||
<td>58.3</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/npid/npid_resnet50_8xb32-steplr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/npid/npid_resnet50_8xb32-steplr-200e_in1k/npid_resnet50_8xb32-steplr-200e_in1k_20220825-a67c5440.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/npid/npid_resnet50_8xb32-steplr-200e_in1k/npid_resnet50_8xb32-steplr-200e_in1k_20220725_161221.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/npid/npid_resnet50_8xb32-steplr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-661b736e.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/npid/npid_resnet50_8xb32-steplr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220728_150535.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td rowspan="3">SimCLR</td>
|
||||
<td>ResNet50</td>
|
||||
<td>200</td>
|
||||
<td>256</td>
|
||||
<td>62.7</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simclr/simclr_resnet50_8xb32-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_8xb32-coslr-200e_in1k/simclr_resnet50_8xb32-coslr-200e_in1k_20220825-15f807a4.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_8xb32-coslr-200e_in1k/simclr_resnet50_8xb32-coslr-200e_in1k_20220721_103223.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-9596a505.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220724_210050.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ResNet50</td>
|
||||
<td>200</td>
|
||||
<td>4096</td>
|
||||
<td>66.9</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simclr/simclr_resnet50_16xb256-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/simclr_resnet50_16xb256-coslr-200e_in1k_20220825-4d9cce50.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/simclr_resnet50_16xb256-coslr-200e_in1k_20220721_150508.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-f12c0457.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220724_172050.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ResNet50</td>
|
||||
<td>800</td>
|
||||
<td>4096</td>
|
||||
<td>69.2</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simclr/simclr_resnet50_16xb256-coslr-800e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/simclr_resnet50_16xb256-coslr-800e_in1k_20220825-85fcc4de.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/simclr_resnet50_16xb256-coslr-800e_in1k_20220725_112248.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-b80ae1e5.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220730_165101.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>MoCo v2</td>
|
||||
<td>ResNet50</td>
|
||||
<td>200</td>
|
||||
<td>256</td>
|
||||
<td>67.5</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/mocov2_resnet50_8xb32-coslr-200e_in1k_20220825-b6d23c86.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/mocov2_resnet50_8xb32-coslr-200e_in1k_20220721_215805.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-994c4128.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220724_172046.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>BYOL</td>
|
||||
<td>ResNet50</td>
|
||||
<td>200</td>
|
||||
<td>4096</td>
|
||||
<td>71.8</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/byol/byol_resnet50_16xb256-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/byol/byol_resnet50_16xb256-coslr-200e_in1k/byol_resnet50_16xb256-coslr-200e_in1k_20220825-de817331.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/byol/byol_resnet50_16xb256-coslr-200e_in1k/byol_resnet50_16xb256-coslr-200e_in1k_20220721_150515.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/byol/byol_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-7596c6f5.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/byol/byol_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220724_130251.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>SwAV</td>
|
||||
<td>ResNet50</td>
|
||||
<td>200</td>
|
||||
<td>256</td>
|
||||
<td>70.5</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96_20220825-5b3fc7fc.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96_20220728_141003.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220825-80341e08.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220802_145230.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>DenseCL</td>
|
||||
<td>ResNet50</td>
|
||||
<td>200</td>
|
||||
<td>256</td>
|
||||
<td>63.5</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/densecl/densecl_resnet50_8xb32-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/densecl/densecl_resnet50_8xb32-coslr-200e_in1k/densecl_resnet50_8xb32-coslr-200e_in1k_20220825-3078723b.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/densecl/densecl_resnet50_8xb32-coslr-200e_in1k/densecl_resnet50_8xb32-coslr-200e_in1k_20220727_221415.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/densecl/densecl_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-f0f0a579.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/densecl/densecl_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220730_091650.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td rowspan="2">SimSiam</td>
|
||||
<td>ResNet50</td>
|
||||
<td>100</td>
|
||||
<td>256</td>
|
||||
<td>68.3</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/simsiam_resnet50_8xb32-coslr-100e_in1k_20220825-d07cb2e6.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/simsiam_resnet50_8xb32-coslr-100e_in1k_20220725_224724.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-f53ba400.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220804_175115.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ResNet50</td>
|
||||
<td>200</td>
|
||||
<td>256</td>
|
||||
<td>69.8</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/simsiam_resnet50_8xb32-coslr-200e_in1k_20220825-efe91299.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/simsiam_resnet50_8xb32-coslr-200e_in1k_20220726_033722.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-519b5135.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220802_120717.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>BarlowTwins</td>
|
||||
<td>ResNet50</td>
|
||||
<td>300</td>
|
||||
<td>2048</td>
|
||||
<td>71.8</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k/barlowtwins_resnet50_8xb256-coslr-300e_in1k_20220825-57307488.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k/barlowtwins_resnet50_8xb256-coslr-300e_in1k_20220726_033718.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220825-52fde35f.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220730_093018.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td rowspan="6">MoCo v3</td>
|
||||
<td>ResNet50</td>
|
||||
<td>100</td>
|
||||
<td>4096</td>
|
||||
<td>69.6</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/mocov3_resnet50_8xb512-amp-coslr-100e_in1k_20220927-f1144efa.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/mocov3_resnet50_8xb512-amp-coslr-100e_in1k_20220915_154635.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-8f7d937e.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220920_113350.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ResNet50</td>
|
||||
<td>300</td>
|
||||
<td>4096</td>
|
||||
<td>72.8</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/mocov3_resnet50_8xb512-amp-coslr-300e_in1k_20220927-1e4f3304.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/mocov3_resnet50_8xb512-amp-coslr-300e_in1k_20220915_180538.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-d21ddac2.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220920_113403.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ResNet50</td>
|
||||
<td>800</td>
|
||||
<td>4096</td>
|
||||
<td>74.4</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/mocov3_resnet50_8xb512-amp-coslr-800e_in1k_20220927-e043f51a.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/mocov3_resnet50_8xb512-amp-coslr-800e_in1k_20220919_111209.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-0e97a483.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220926_102021.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-small</td>
|
||||
<td>300</td>
|
||||
<td>4096</td>
|
||||
<td>73.6</td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k-224_20220826-08bc52f7.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k-224_20220721_153833.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-small-p16_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k_20220826-376674ef.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k_20220724_140850.json'>log</a></td>
|
||||
<td>/</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-base</td>
|
||||
<td>300</td>
|
||||
<td>4096</td>
|
||||
<td>76.9</td>
|
||||
<td>83.0</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k-224_20220826-25213343.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k-224_20220725_104223.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k_20220826-83be7758.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k_20220729_004628.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb64-coslr-150e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k_20220826-f1e6c442.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k_20220809_103500.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-large</td>
|
||||
<td>300</td>
|
||||
<td>4096</td>
|
||||
<td>/</td>
|
||||
<td>83.7</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k-224_20220829-9b88a442.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k-224_20220818_143032.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_ft-8xb64-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k_20220829-878a2f7f.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k_20220825_201433.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td rowspan="9">MAE</td>
|
||||
<td>ViT-base</td>
|
||||
<td>300</td>
|
||||
<td>4096</td>
|
||||
<td>60.8</td>
|
||||
<td>83.1</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220829-c2cf66ba.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220718_152424.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220720_104514.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220713_140138.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-base</td>
|
||||
<td>400</td>
|
||||
<td>4096</td>
|
||||
<td>62.5</td>
|
||||
<td>83.3</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-400e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k/mae_vit-base-p16_8xb512-coslr-400e-fp16_in1k_20220825-bc79e40b.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k/mae_vit-base-p16_8xb512-coslr-400e-fp16_in1k_20220628_200815.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220713_142534.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220708_183134.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-base</td>
|
||||
<td>800</td>
|
||||
<td>4096</td>
|
||||
<td>65.1</td>
|
||||
<td>83.3</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-800e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k/mae_vit-base-p16_8xb512-coslr-800e-fp16_in1k_20220825-5d81fbc4.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k/mae_vit-base-p16_8xb512-coslr-800e-fp16_in1k_20220718_134405.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k20220721_203941.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220724_232940.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-base</td>
|
||||
<td>1600</td>
|
||||
<td>4096</td>
|
||||
<td>67.1</td>
|
||||
<td>83.5</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-1600e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k_20220825-f7569ca2.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k_20220815_103458.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220724_232557.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220825-cf70aa21.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220721_202304.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-large</td>
|
||||
<td>400</td>
|
||||
<td>4096</td>
|
||||
<td>70.7</td>
|
||||
<td>85.2</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-large-p16_8xb512-amp-coslr-400e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k_20220825-b11d0425.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k_20220726_202204.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k_20220803_101331.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_ft-8xb128-coslr-50e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k_20220729_122511.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-large</td>
|
||||
<td>800</td>
|
||||
<td>4096</td>
|
||||
<td>73.7</td>
|
||||
<td>85.4</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-large-p16_8xb512-amp-coslr-800e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k_20220825-df72726a.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k_20220804_104018.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k_20220808_092730.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_ft-8xb128-coslr-50e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k_20220730_235819.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-large</td>
|
||||
<td>1600</td>
|
||||
<td>4096</td>
|
||||
<td>75.5</td>
|
||||
<td>85.7</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-large-p16_8xb512-amp-coslr-1600e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k_20220825-cc7e98c9.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k_20220806_210725.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k_20220813_155615.json'>log</a></td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_ft-8xb128-coslr-50e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k_20220813_125305.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-huge-FT-224</td>
|
||||
<td>1600</td>
|
||||
<td>4096</td>
|
||||
<td>/</td>
|
||||
<td>86.9</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-huge-p16_8xb512-amp-coslr-1600e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k_20220916-ff848775.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k_20220814_135241.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-huge-p16_ft-8xb128-coslr-50e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/vit-huge-p16_ft-8xb128-coslr-50e_in1k/vit-huge-p16_ft-8xb128-coslr-50e_in1k_20220916-0bfc9bfd.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/vit-huge-p16_ft-8xb128-coslr-50e_in1k/vit-huge-p16_ft-8xb128-coslr-50e_in1k_20220829_114027.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>ViT-huge-FT-448</td>
|
||||
<td>1600</td>
|
||||
<td>4096</td>
|
||||
<td>/</td>
|
||||
<td>87.3</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-huge-p16_8xb512-amp-coslr-1600e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k_20220916-ff848775.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k_20220814_135241.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448_20220916-95b6a0ce.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448_20220913_113737.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>CAE</td>
|
||||
<td>ViT-base</td>
|
||||
<td>300</td>
|
||||
<td>2048</td>
|
||||
<td>/</td>
|
||||
<td>83.3</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/cae/cae_vit-base-p16_16xb128-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k_20220825-404a1929.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k_20220615_163141.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k_20220825-f3d234cd.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k_20220711_165500.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td rowspan="4">SimMIM</td>
|
||||
<td>Swin-base-FT192</td>
|
||||
<td>100</td>
|
||||
<td>2048</td>
|
||||
<td>/</td>
|
||||
<td>82.7</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simmim/simmim_swin-base_16xb128-amp-coslr-100e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220829-0e15782d.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220827_034052.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/swin-base_ft-8xb256-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k/swin-base_ft-8xb256-coslr-100e_in1k_20220829-9cf23aa1.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k/swin-base_ft-8xb256-coslr-100e_in1k_20220829_001452.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>Swin-base-FT224</td>
|
||||
<td>100</td>
|
||||
<td>2048</td>
|
||||
<td>/</td>
|
||||
<td>83.5</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simmim/simmim_swin-base_16xb128-amp-coslr-100e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220829-0e15782d.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220827_034052.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/swin-base_ft-8xb256-coslr-100e_in1k-224.py'>config</a> | model | log</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>Swin-base-FT224</td>
|
||||
<td>800</td>
|
||||
<td>2048</td>
|
||||
<td>/</td>
|
||||
<td>83.8</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192_20220916-a0e931ac.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192_20220906_141645.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/swin-base_ft-8xb256-coslr-100e_in1k-224.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k-224/swin-base_ft-8xb256-coslr-100e_in1k-224_20220916-b202cd1c.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k-224/swin-base_ft-8xb256-coslr-100e_in1k-224_20220909_104645.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>Swin-large-FT224</td>
|
||||
<td>800</td>
|
||||
<td>2048</td>
|
||||
<td>/</td>
|
||||
<td>84.8</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192_20220916-4ad216d3.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192_20220907_203738.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224_20220916-d4865790.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224_20220914_133331.json'>log</a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>MaskFeat</td>
|
||||
<td>ViT-base</td>
|
||||
<td>300</td>
|
||||
<td>2048</td>
|
||||
<td>/</td>
|
||||
<td>83.4</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221101-6dfc8bf3.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221019_194256.json'>log</a></td>
|
||||
<td>/</td>
|
||||
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb256-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb256-coslr-100e_in1k/vit-base-p16_ft-8xb256-coslr-100e_in1k_20221028-5134431c.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb256-coslr-100e_in1k/vit-base-p16_ft-8xb256-coslr-100e_in1k_20221026_105344.json'>log</a></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
|
|
|||
Loading…
Reference in New Issue