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# Model Zoo
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## Pre-trained model download links
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< table >
< thead >
< tr >
< th > Method< / th >
< th > Config< / th >
< th > Remarks< / th >
< th > Download link< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > < a href = "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py" target = "_blank" rel = "noopener noreferrer" > ImageNet< / a > < / td >
< td > -< / td >
< td > torchvision< / td >
< td > < a href = "https://drive.google.com/file/d/11xA3TOcbD0qOrwpBfYonEDeseE1wMfBh/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > imagenet_r50-21352794.pth< / a > < / td >
< / tr >
< tr >
< td > Random< / td >
< td > -< / td >
< td > kaiming< / td >
< td > < a href = "https://drive.google.com/file/d/1UaFTjd6sbKkZEE-f58Zv30bnx7C1qJBb/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > random_r50-5d0fa71b.pth< / a > < / td >
< / tr >
< tr >
< td > < a href = "https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Doersch_Unsupervised_Visual_Representation_ICCV_2015_paper.pdf" target = "_blank" rel = "noopener noreferrer" > Relative-Loc< / a > < / td >
< td > selfsup/relative_loc/r50.py< / td >
< td > default< / td >
< td > < / td >
< / tr >
< tr >
< td > < a href = "https://arxiv.org/abs/1803.07728" target = "_blank" rel = "noopener noreferrer" > Rotation-Pred< / a > < / td >
< td > selfsup/rotation_pred/r50.py< / td >
< td > default< / td >
< td > < a href = "https://drive.google.com/file/d/1t3oClmIvQ0p8RZ0V5yvQFltzjqBO823Y/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > rotation_r50-cfab8ebb.pth< / a > < / td >
< / tr >
< tr >
< td > < a href = "https://arxiv.org/abs/1807.05520" target = "_blank" rel = "noopener noreferrer" > DeepCluster< / a > < / td >
< td > selfsup/deepcluster/r50.py< / td >
< td > default< / td >
< td > < a href = "https://drive.google.com/file/d/1GxgP7pI18JtFxDIC0hnHOanvUYajoLlg/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > deepcluster_r50-bb8681e2.pth< / a > < / td >
< / tr >
< tr >
< td > < a href = "https://arxiv.org/abs/1805.01978" target = "_blank" rel = "noopener noreferrer" > NPID< / a > < / td >
< td > selfsup/npid/r50.py< / td >
< td > default< / td >
< td > < a href = "https://drive.google.com/file/d/1sm6I3Y5XnCWdbmeLSF4YupUtPe5nRQMI/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > npid_r50-dec3df0c.pth< / a > < / td >
< / tr >
< tr >
< td > < / td >
< td > selfsup/npid/r50_ensure_neg.py< / td >
< td > default< / td >
< td > < a href = "https://drive.google.com/file/d/1FldDrb6kzF3CZ7737mwCXVI6HE2aCSaF/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > npid_r50_ensure_neg-ce09b7ae.pth< / a > < / td >
< / tr >
< tr >
< td > < a href = "http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhan_Online_Deep_Clustering_for_Unsupervised_Representation_Learning_CVPR_2020_paper.pdf" target = "_blank" rel = "noopener noreferrer" > ODC< / a > < / td >
< td > selfsup/odc/r50_v1.py< / td >
< td > default< / td >
< td > < a href = "https://drive.google.com/file/d/1EdhJeZAyMsD_pEW7uMhLzos5xZLdariN/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > odc_r50_v1-5af5dd0c.pth< / a > < / td >
< / tr >
< tr >
< td > < a href = "https://arxiv.org/abs/1911.05722" target = "_blank" rel = "noopener noreferrer" > MoCo< / a > < / td >
< td > selfsup/moco/r50_v1.py< / td >
< td > default< / td >
< td > < a href = "https://drive.google.com/file/d/1ANXfnoT8yBQQBBqR_kQLQorK20l65KMy/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > moco_r50_v1-4ad89b5c.pth< / a > < / td >
< / tr >
< tr >
< td > < a href = "https://arxiv.org/abs/2003.04297" target = "_blank" rel = "noopener noreferrer" > MoCo v2< / a > < / td >
< td > selfsup/moco/r50_v2.py< / td >
< td > default< / td >
< td > < a href = "https://drive.google.com/file/d/1Cc5qMjPkKW6WeM4ic9Tq-IBxswyJhMnF/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > moco_r50_v2-58f10cfe.pth< / a > < / td >
< / tr >
< tr >
< td > < / td >
< td > selfsup/moco/r50_v2_simclr_neck.py< / td >
< td > -> SimCLR neck< br > < / td >
< td > < a href = "https://drive.google.com/file/d/1PnZmCVmFwBv7ZnqMgNYj5DvmbPGM5rCx/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > moco_r50_v2_simclr_neck-70379356.pth< / a > < / td >
< / tr >
< tr >
< td > < a href = "https://arxiv.org/abs/2002.05709" target = "_blank" rel = "noopener noreferrer" > SimCLR< / a > < / td >
< td > selfsup/simclr/r50_bs256_ep200.py< / td >
< td > default< / td >
< td > < a href = "https://drive.google.com/file/d/1aZ43nSdivdNxHbM9DKVoZYVhZ8TNnmPp/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > simclr_r50_bs256_ep200-4577e9a6.pth< / a > < / td >
< / tr >
< tr >
< td > < / td >
< td > selfsup/simclr/r50_bs256_ep200_mocov2_neck.py< / td >
< td > -> MoCo v2 neck< / td >
< td > < a href = "https://drive.google.com/file/d/1AXpSKqgWfnj6jCgN65BXSTCKFfuIVELa/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > simclr_r50_bs256_ep200_mocov2_neck-0d6e5ff2.pth< / a > < / td >
< / tr >
< tr >
< td > < a href = "https://arxiv.org/abs/2006.07733" target = "_blank" rel = "noopener noreferrer" > BYOL< / a > < / td >
< td > selfsup/byol/r50.py< / td >
< td > default< / td >
< td > < / td >
< / tr >
< / tbody >
< / table >
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## Benchmarks
### VOC07 SVM & SVM Low-shot
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< table > < thead > < tr > < th rowspan = "2" > Method< / th > < th rowspan = "2" > Config< / th > < th rowspan = "2" > Remarks< / th > < th rowspan = "2" > Best layer< / th > < th rowspan = "2" > VOC07 SVM< / th > < th colspan = "8" > VOC07 SVM Low-shot< / th > < / tr > < tr > < td > 1< / td > < td > 2< / td > < td > 4< / td > < td > 8< / td > < td > 16< / td > < td > 32< / td > < td > 64< / td > < td > 96< / td > < / tr > < / thead > < tbody > < tr > < td > < a href = "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py" target = "_blank" rel = "noopener noreferrer" > ImageNet< / a > < / td > < td > -< / td > < td > torchvision< / td > < td > feat5< / td > < td > 87.17< / td > < td > 52.99< / td > < td > 63.55< / td > < td > 73.7< / td > < td > 78.79< / td > < td > 81.76< / td > < td > 83.75< / td > < td > 85.18< / td > < td > 85.97< / td > < / tr > < tr > < td > Random< / td > < td > -< / td > < td > kaiming< / td > < td > feat2< / td > < td > 30.22< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Doersch_Unsupervised_Visual_Representation_ICCV_2015_paper.pdf" target = "_blank" rel = "noopener noreferrer" > Relative-Loc< / a > < / td > < td > < / td > < td > < / td > < td > feat5< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1803.07728" target = "_blank" rel = "noopener noreferrer" > Rotation-Pred< / a > < / td > < td > selfsup/rotation_pred/r50.py< / td > < td > default< / td > < td > feat4< / td > < td > 67.38< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1807.05520" target = "_blank" rel = "noopener noreferrer" > DeepCluster< / a > < / td > < td > selfsup/deepcluster/r50.py< / td > < td > default< / td > < td > feat5< / td > < td > 74.26< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1805.01978" target = "_blank" rel = "noopener noreferrer" > NPID< / a > < / td > < td > selfsup/npid/r50.py< / td > < td > default< / td > < td > feat5< / td > < td > 74.50< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < / td > < td > selfsup/npid/r50_ensure_neg.py< / td > < td > ensure_neg=True< / td > < td > feat5< / td > < td > 75.70< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhan_Online_Deep_Clustering_for_Unsupervised_Representation_Learning_CVPR_2020_paper.pdf" target = "_blank" rel = "noopener noreferrer" > ODC< / a > < / td > < td > selfsup/odc/r50_v1.py< / td > < td > default< / td > < td > feat5< / td > < td > 78.42< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1911.05722" target = "_blank" rel = "noopener noreferrer" > MoCo< / a > < / td > < td > selfsup/moco/r50_v1.py< / td > < td > default< / td > < td > feat5< / td > < td > 79.18< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2003.04297" target = "_blank" rel = "noopener noreferrer" > MoCo v2< / a > < / td > < td > selfsup/moco/r50_v2.py< / td > < td > default< / td > < td > feat5< / td > < td > 84.05< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < / td > < td > selfsup/moco/r50_v2_simclr_neck.py< / td > < td > -> SimCLR neck< br > < / td > < td > feat5< / td > < td > 84.00< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2002.05709" target = "_blank" rel = "noopener noreferrer" > SimCLR< / a > < / td > < td > selfsup/simclr/r50_bs256_ep200.py< / td > < td > default< / td > < td > feat5< / td > < td > 78.95< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < / td > < td > selfsup/simclr/r50_bs256_ep200_mocov2_neck.py< / td > < td > -> MoCo v2 neck< / td > < td > feat5< / td > < td > 77.65< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2006.07733" target = "_blank" rel = "noopener noreferrer" > BYOL< / a > < / td > < td > selfsup/byol/r50.py< / td > < td > default< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < / tbody > < / table >
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### ImageNet Linear Classification
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**Note**
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* Config: `configs/benchmarks/linear_classification/imagenet/r50_multihead.py` for ImageNet (Multi) and `configs/benchmarks/linear_classification/imagenet/r50_moco.py` for ImageNet (Last).
* For DeepCluster, use the corresponding one with `_sobel` .
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* ImageNet (Multi) evaluates features in around 9k dimensions from different layers. Top-1 result of the last epoch is reported.
* ImageNet (Last) evaluates the last feature after global average pooling, e.g., 2048 dimensions for resnet50. The best top-1 result among all epochs is reported.
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< table > < thead > < tr > < th rowspan = "2" > Method< / th > < th rowspan = "2" > Config< / th > < th rowspan = "2" > Remarks< / th > < th colspan = "5" > ImageNet (Multi)< / th > < th > ImageNet (Last)< / th > < / tr > < tr > < td > feat1< / td > < td > feat2< / td > < td > feat3< / td > < td > feat4< / td > < td > feat5< / td > < td > avgpool< / td > < / tr > < / thead > < tbody > < tr > < td > < a href = "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py" target = "_blank" rel = "noopener noreferrer" > ImageNet< / a > < / td > < td > -< / td > < td > torchvision< / td > < td > 15.18< / td > < td > 33.96< / td > < td > 47.86< / td > < td > 67.56< / td > < td > 76.17< / td > < td > 74.12< / td > < / tr > < tr > < td > Random< / td > < td > -< / td > < td > kaiming< / td > < td > 11.37< / td > < td > 16.21< / td > < td > 13.47< / td > < td > 9.07< / td > < td > 6.54< / td > < td > 4.35< / td > < / tr > < tr > < td > < a href = "https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Doersch_Unsupervised_Visual_Representation_ICCV_2015_paper.pdf" target = "_blank" rel = "noopener noreferrer" > Relative-Loc< / a > < / td > < td > selfsup/relative_loc/r50.py< / td > < td > default< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1803.07728" target = "_blank" rel = "noopener noreferrer" > Rotation-Pred< / a > < / td > < td > selfsup/rotation_pred/r50.py< / td > < td > default< / td > < td > 12.89< / td > < td > 34.30< / td > < td > 44.91< / td > < td > 54.99< / td > < td > 49.09< / td > < td > 47.01< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1807.05520" target = "_blank" rel = "noopener noreferrer" > DeepCluster< / a > < / td > < td > selfsup/deepcluster/r50.py< / td > < td > default< / td > < td > 12.78< / td > < td > 30.81< / td > < td > 43.88< / td > < td > 57.71< / td > < td > 51.68< / td > < td > 46.92< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1805.01978" target = "_blank" rel = "noopener noreferrer" > NPID< / a > < / td > < td > selfsup/npid/r50.py< / td > < td > default< / td > < td > 14.28< / td > < td > 31.20< / td > < td > 40.68< / td > < td > 54.46< / td > < td > 56.61< / td > < td > 56.60< / td > < / tr > < tr > < td > < a href = "http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhan_Online_Deep_Clustering_for_Unsupervised_Representation_Learning_CVPR_2020_paper.pdf" target = "_blank" rel = "noopener noreferrer" > ODC< / a > < / td > < td > selfsup/odc/r50_v1.py< / td > < td > default< / td > < td > 14.76< / td > < td > 31.82< / td > < td > 42.44< / td > < td > 55.76< / td > < td > 57.70< / td > < td > 53.42< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1911.05722" target = "_blank" rel = "noopener noreferrer" > MoCo< / a > < / td > < td > selfsup/moco/r50_v1.py< / td > < td > default< / td > < td > 15.32< / td > < td > 33.08< / td > < td > 44.68< / td > < td > 57.27< / td > < td > 60.60< / td > < td > 61.02< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2003.04297" target = "_blank" rel = "noopener noreferrer" > MoCo v2< / a > < / td > < td > selfsup/moco/r50_v2.py< / td > < td > default< / td > < td > 15.35< / td > < td > 34.57< / td > < td > 45.81< / td > < td > 60.96< / td > < td > 66.72< / td > < td > 67.02< / td > < / tr > < tr > < td > < / td > < td > selfsup/moco/r50_v2_simclr_neck.py< / td > < td > -> SimCLR neck< br > < / td > < td > 15.19< / td > < td > 32.54< / td > < td > 43.12< / td > < td > 60.36< / td > < td > 67.08< / td > < td > 65.39< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2002.05709" target = "_blank" rel = "noopener noreferrer" > SimCLR< / a > < / td > < td > selfsup/simclr/r50_bs256_ep200.py< / td > < td > default< / td > < td > 17.09< / td > < td > 31.37< / td > < td > 41.38< / td > < td > 54.35< / td > < td > 61.57< / td > < td > 60.06< / td > < / tr > < tr > < td > < / td > < td > selfsup/simclr/r50_bs256_ep200_mocov2_neck.py< / td > < td > -> MoCo v2 neck< / td > < td > 16.97< / td > < td > 31.88< / td > < td > 41.73< / td > < td > 54.33< / td > < td > 59.94< / td > < td > 58.00< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2006.07733" target = "_blank" rel = "noopener noreferrer" > BYOL< / a > < / td > < td > selfsup/byol/r50.py< / td > < td > default< / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < / tbody > < / table >
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2020-07-08 14:03:42 +08:00
### Places205 Linear Classification
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2020-06-29 12:51:06 +08:00
Coming soon.
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### ImageNet Semi-Supervised Classification
**Note**
* In this benchmark, the necks or heads are removed and only the backbone CNN is evaluated by appending a linear classification head. All parameters are fine-tuned.
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* Config: under `configs/benchmarks/semi_classification/imagenet_1percent/` for 1% data, and `configs/benchmarks/semi_classification/imagenet_10percent/` for 10% data.
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* When training with 1% ImageNet, we find hyper-parameters especially the learning rate greatly influence the performance. Hence, we prepare a list of settings with the base learning rate from \{0.001, 0.01, 0.1\} and the learning rate multiplier for the head from \{1, 10, 100\}. We choose the best performing setting for each method.
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* Please use `--deterministic` in this benchmark.
2020-07-06 21:49:17 +08:00
2020-07-07 21:21:11 +08:00
< table > < thead > < tr > < th rowspan = "2" > Method< / th > < th rowspan = "2" > Config< / th > < th rowspan = "2" > Remarks< / th > < th rowspan = "2" > Optimal setting for ImageNet 1%< / th > < th colspan = "2" > ImageNet 1%< / th > < / tr > < tr > < td > top-1< / td > < td > top-5< / td > < / tr > < / thead > < tbody > < tr > < td > < a href = "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py" target = "_blank" rel = "noopener noreferrer" > ImageNet< / a > < / td > < td > -< / td > < td > torchvision< / td > < td > r50_lr0_001_head100.py< / td > < td > 68.68< / td > < td > 88.87< / td > < / tr > < tr > < td > Random< / td > < td > -< / td > < td > kaiming< / td > < td > r50_lr0_01_head1.py< / td > < td > 1.56< / td > < td > 4.99< / td > < / tr > < tr > < td > < a href = "https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Doersch_Unsupervised_Visual_Representation_ICCV_2015_paper.pdf" target = "_blank" rel = "noopener noreferrer" > Relative-Loc< / a > < / td > < td > selfsup/relative_loc/r50.py< / td > < td > default< / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1803.07728" target = "_blank" rel = "noopener noreferrer" > Rotation-Pred< / a > < / td > < td > selfsup/rotation_pred/r50.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 18.98< / td > < td > 44.05< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1807.05520" target = "_blank" rel = "noopener noreferrer" > DeepCluster< / a > < / td > < td > selfsup/deepcluster/r50.py< / td > < td > default< / td > < td > r50_lr0_01_head1_sobel.py< / td > < td > 33.44< / td > < td > 58.62< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1805.01978" target = "_blank" rel = "noopener noreferrer" > NPID< / a > < / td > < td > selfsup/npid/r50.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 27.95< / td > < td > 54.37< / td > < / tr > < tr > < td > < a href = "http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhan_Online_Deep_Clustering_for_Unsupervised_Representation_Learning_CVPR_2020_paper.pdf" target = "_blank" rel = "noopener noreferrer" > ODC< / a > < / td > < td > selfsup/odc/r50_v1.py< / td > < td > default< / td > < td > r50_lr0_1_head100.py< / td > < td > 32.39< / td > < td > 61.02< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1911.05722" target = "_blank" rel = "noopener noreferrer" > MoCo< / a > < / td > < td > selfsup/moco/r50_v1.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 33.15< / td > < td > 61.30< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2003.04297" target = "_blank" rel = "noopener noreferrer" > MoCo v2< / a > < / td > < td > selfsup/moco/r50_v2.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 38.71< / td > < td > 67.90< / td > < / tr > < tr > < td > < / td > < td > selfsup/moco/r50_v2_simclr_neck.py< / td > < td > -> SimCLR neck< br > < / td > < td > r50_lr0_01_head100.py< / td > < td > 31.37< br > < / td > < td > 59.65< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2002.05709" target = "_blank" rel = "noopener noreferrer" > SimCLR< / a > < / td > < td > selfsup/simclr/r50_bs256_ep200.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 36.09< / td > < td > 64.50< / td > < / tr > < tr > < td > < / td > < td > selfsup/simclr/r50_bs256_ep200_mocov2_neck.py< / td > < td > -> MoCo v2 neck< / td > < td > r50_lr0_01_head100.py< / td > < td > 36.31< / td > < td > 64.68< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2006.07733" target = "_blank" rel = "noopener noreferrer" > BYOL< / a > < / td > < td > selfsup/byol/r50.py< / td > < td > default< / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < / tbody > < / table >
2020-07-06 21:49:17 +08:00
2020-07-10 23:31:23 +08:00
< table > < thead > < tr > < th rowspan = "2" > Method< / th > < th rowspan = "2" > Config< / th > < th rowspan = "2" > Remarks< / th > < th rowspan = "2" > Optimal setting for ImageNet 10%< / th > < th colspan = "2" > ImageNet 10%< / th > < / tr > < tr > < td > top-1< / td > < td > top-5< / td > < / tr > < / thead > < tbody > < tr > < td > < a href = "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py" target = "_blank" rel = "noopener noreferrer" > ImageNet< / a > < / td > < td > -< / td > < td > torchvision< / td > < td > r50_lr0_001_head10.py< / td > < td > 74.53< / td > < td > 92.19< / td > < / tr > < tr > < td > Random< / td > < td > -< / td > < td > kaiming< / td > < td > r50_lr0_01_head1.py< / td > < td > 21.78< / td > < td > 44.24< / td > < / tr > < tr > < td > < a href = "https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Doersch_Unsupervised_Visual_Representation_ICCV_2015_paper.pdf" target = "_blank" rel = "noopener noreferrer" > Relative-Loc< / a > < / td > < td > selfsup/relative_loc/r50.py< / td > < td > default< / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1803.07728" target = "_blank" rel = "noopener noreferrer" > Rotation-Pred< / a > < / td > < td > selfsup/rotation_pred/r50.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 54.75< / td > < td > 80.21< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1807.05520" target = "_blank" rel = "noopener noreferrer" > DeepCluster< / a > < / td > < td > selfsup/deepcluster/r50.py< / td > < td > default< / td > < td > r50_lr0_01_head1_sobel.py< / td > < td > 52.94< / td > < td > 77.96< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1805.01978" target = "_blank" rel = "noopener noreferrer" > NPID< / a > < / td > < td > selfsup/npid/r50.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 57.22< / td > < td > 81.39< / td > < / tr > < tr > < td > < a href = "http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhan_Online_Deep_Clustering_for_Unsupervised_Representation_Learning_CVPR_2020_paper.pdf" target = "_blank" rel = "noopener noreferrer" > ODC< / a > < / td > < td > selfsup/odc/r50_v1.py< / td > < td > default< / td > < td > r50_lr0_1_head10.py< / td > < td > 58.15< / td > < td > 82.55< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/1911.05722" target = "_blank" rel = "noopener noreferrer" > MoCo< / a > < / td > < td > selfsup/moco/r50_v1.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 60.08< / td > < td > 84.02< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2003.04297" target = "_blank" rel = "noopener noreferrer" > MoCo v2< / a > < / td > < td > selfsup/moco/r50_v2.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 61.64< / td > < td > 84.90< / td > < / tr > < tr > < td > < / td > < td > selfsup/moco/r50_v2_simclr_neck.py< / td > < td > -> SimCLR neck< br > < / td > < td > < / td > < td > 60.60< / td > < td > 84.29< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2002.05709" target = "_blank" rel = "noopener noreferrer" > SimCLR< / a > < / td > < td > selfsup/simclr/r50_bs256_ep200.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 58.46< / td > < td > 82.60< / td > < / tr > < tr > < td > < / td > < td > selfsup/simclr/r50_bs256_ep200_mocov2_neck.py< / td > < td > -> MoCo v2 neck< / td > < td > < / td > < td > 58.38< / td > < td > 82.53< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2006.07733" target = "_blank" rel = "noopener noreferrer" > BYOL< / a > < / td > < td > selfsup/byol/r50.py< / td > < td > default< / td > < td > < / td > < td > < / td > < td > < / td > < / tr > < / tbody > < / table >
2020-06-29 00:10:34 +08:00
### PASCAL VOC07+12 Object Detection
2020-06-29 12:51:06 +08:00
Coming soon.
