2020-06-29 00:10:34 +08:00
# Model Zoo
2020-06-22 22:05:14 +08:00
2020-06-29 00:10:34 +08:00
## Pre-trained model download links
2020-06-22 22:05:14 +08:00
2020-08-13 00:15:11 +08:00
< 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 > < a href = "https://drive.google.com/file/d/1ibk1BI3PFQxZqcxuDfHs3n7JnWKCgl8x/view?usp=sharing" target = "_blank" rel = "noopener noreferrer" > relative_loc_r50-342c9097.pth< / a > < / 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 > < 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
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## Benchmarks
### VOC07 SVM & SVM Low-shot
2020-08-31 21:22:57 +08:00
< 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 > 30.54< / td > < td > 9.15< / td > < td > 9.39< / td > < td > 11.09< / td > < td > 12.3< / td > < td > 14.3< / td > < td > 17.41< / td > < td > 21.32< / td > < td > 23.77< / 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 > feat4< / td > < td > 64.78< / td > < td > 18.17< / td > < td > 22.08< / td > < td > 29.37< / td > < td > 35.58< / td > < td > 41.8< / td > < td > 48.73< / td > < td > 55.55< / td > < td > 58.33< / 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 > 18.91< / td > < td > 23.33< / td > < td > 30.57< / td > < td > 38.22< / td > < td > 45.83< / td > < td > 52.23< / td > < td > 58.08< / td > < td > 61.11< / 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 > 29.73< / td > < td > 37.66< / td > < td > 45.85< / td > < td > 55.57< / td > < td > 62.48< / td > < td > 66.15< / td > < td > 70.0< / td > < td > 71.37< / 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 > 24.19< / td > < td > 31.24< / td > < td > 39.69< / td > < td > 50.99< / td > < td > 59.03< / td > < td > 64.4< / td > < td > 68.69< / td > < td > 70.84< / 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 > 32.42< / td > < td > 40.27< / td > < td > 49.95< / td > < td > 59.96< / td > < td > 65.71< / td > < td > 69.99< / td > < td > 73.64< / td > < td > 75.13< / 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 > 30.03< / td > < td > 37.73< / td > < td > 47.64< / td > < td > 58.78< / td > < td > 66.0< / td > < td > 70.6< / td > < td > 74.6< / td > < td > 76.07< / 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 > 42.33< / td > < td > 50.57< / td > < td > 62.59< / td > < td > 70.47< / td > < td > 75.82< / td > < td > 78.53< / td > < td > 80.9< / td > < td > 81.99< / td > < / tr > < tr > < td > < / td > < td > selfsup/moco/r50_v2_simclr_neck.py< / td > < td > -> SimCLR neck< / 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 > 32.45< / td > < td > 40.76< / td > < td > 50.4< / td > < td > 59.01< / td > < td > 65.45< / td > < td > 70.13< / td > < td > 73.58< / td > < td > 75.35< / 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 =
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### ImageNet Linear Classification
2020-07-07 21:24:34 +08:00
**Note**
2020-07-28 00:16:14 +08:00
* Config: `configs/benchmarks/linear_classification/imagenet/r50_multihead.py` for ImageNet (Multi) and `configs/benchmarks/linear_classification/imagenet/r50_last.py` for ImageNet (Last).
2020-07-04 15:24:27 +08:00
* For DeepCluster, use the corresponding one with `_sobel` .
2020-07-04 15:20:10 +08:00
* 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.
2020-08-31 23:27:27 +08:00
< 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 > 14.76< / td > < td > 31.29< / td > < td > 45.77< / td > < td > 49.31< / td > < td > 40.20< / td > < td > 38.83< / 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_bs4096_ep200.py< / td > < td > default< / td > < td > 16.70< / td > < td > 34.22< / td > < td > 46.61< / td > < td > 60.78< / td > < td > 69.14< / td > < td > 67.10< / td > < / tr > < / tbody > < / table >
2020-06-29 00:10:34 +08:00
2020-07-08 14:03:42 +08:00
### Places205 Linear Classification
2020-06-29 00:10:34 +08:00
2020-09-01 00:58:51 +08:00
**Note**
* Config: `configs/benchmarks/linear_classification/places205/r50_multihead.py` .
* For DeepCluster, use the corresponding one with `_sobel` .
* Places205 evaluates features in around 9k dimensions from different layers. Top-1 result of the last epoch is reported.
< table > < thead > < tr > < th rowspan = "2" > Method< / th > < th rowspan = "2" > Config< / th > < th rowspan = "2" > Remarks< / th > < th colspan = "5" > Places205< / th > < / tr > < tr > < td > feat1< / td > < td > feat2< / td > < td > feat3< / td > < td > feat4< / td > < td > feat5< / 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 > 21.27< / td > < td > 36.10< / td > < td > 43.03< / td > < td > 51.38< / td > < td > 53.05< / td > < / tr > < tr > < td > Random< / td > < td > -< / td > < td > kaiming< / td > < td > 17.19< / td > < td > 21.70< / td > < td > 19.23< / td > < td > 14.59< / td > < td > 11.73< / 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 > 21.07< / td > < td > 34.86< / td > < td > 42.84< / td > < td > 45.71< / td > < td > 41.45< / 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 > 18.65< / td > < td > 35.71< / td > < td > 42.28< / td > < td > 45.98< / td > < td > 43.72< / 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 > 18.80< / td > < td > 33.93< / td > < td > 41.44< / td > < td > 47.22< / td > < td > 42.61< / 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 > 20.53< / td > < td > 34.03< / td > < td > 40.48< / td > < td > 47.13< / td > < td > 47.73< / td > < / tr > < tr > < td > < a href = "https://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 > 20.94< / td > < td > 34.78< / td > < td > 41.19< / td > < td > 47.45< / td > < td > 49.18< / 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 > 21.13< / td > < td > 35.19< / td > < td > 42.40< / td > < td > 48.78< / td > < td > 50.70< / 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 > 20.86< / td > < td > 35.63< / td > < td > 42.57< / td > < td > 49.93< / td > < td > 52.05< / td > < / tr > < tr > < td > < / td > < td > selfsup/moco/r50_v2_simclr_neck.py< / td > < td > -> SimCLR neck< / 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 > 22.55< / td > < td > 34.14< / td > < td > 40.35< / td > < td > 47.15< / td > < td > 51.64< / td > < / tr > < tr > < td > < / td > < td > selfsup/simclr/r50_bs256_ep200_mocov2_neck.py< / td > < td > -> MoCo v2 neck< / 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_bs4096_ep200.py< / td > < td > default< / td > < td > 22.28< / td > < td > 35.95< / td > < td > 43.03< / td > < td > 49.79< / td > < td > 52.75< / td > < / tr > < / tbody > < / table >
2020-06-29 00:10:34 +08:00
### 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.
2020-07-04 15:24:27 +08:00
* Config: under `configs/benchmarks/semi_classification/imagenet_1percent/` for 1% data, and `configs/benchmarks/semi_classification/imagenet_10percent/` for 10% data.
2020-07-06 21:49:17 +08:00
* 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.
2020-06-29 00:10:34 +08:00
* Please use `--deterministic` in this benchmark.
2020-07-06 21:49:17 +08:00
2020-08-31 23:27:27 +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 > r50_lr0_01_head100.py< / td > < td > 16.48< / td > < td > 40.37< / 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_bs4096_ep200.py< / td > < td > default< / td > < td > r50_lr0_01_head10.py< / td > < td > 49.37< / td > < td > 76.75< / td > < / tr > < / tbody > < / table >
2020-07-06 21:49:17 +08:00
2020-08-31 23:27:27 +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 > r50_lr0_01_head100.py< / td > < td > 53.86< / td > < td > 79.62< / 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_bs4096_ep200.py< / td > < td > default< / td > < td > r50_lr0_01_head100.py< / td > < td > 65.94< / td > < td > 87.81< / 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
2020-08-06 10:47:04 +08:00
**Note**
* This benchmark follows the evluation protocols set up by MoCo.
* Config: `benchmarks/detection/configs/pascal_voc_R_50_C4_24k_moco.yaml` .
* Please follow [here ](GETTING_STARTED.md#voc0712--coco17-object-detection ) to run the evaluation.
2020-08-31 23:27:27 +08:00
< table > < thead > < tr > < th rowspan = "2" > Method< / th > < th rowspan = "2" > Config< / th > < th rowspan = "2" > Remarks< / th > < th colspan = "3" > VOC07+12< / th > < / tr > < tr > < td > AP50< / td > < td > AP< / td > < td > AP75< / 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 > 81.58< / td > < td > 54.19< / td > < td > 59.80< / td > < / tr > < tr > < td > Random< / td > < td > -< / td > < td > kaiming< / td > < td > 59.02< / td > < td > 32.83< / td > < td > 31.60< / 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 > 80.36< / td > < td > 55.13< / td > < td > 61.18< / 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 > 80.91< / td > < td > 55.52< / td > < td > 61.39< / 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 > 80.03< / td > < td > 54.11< / td > < td > 59.50< / 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 > 81.38< / td > < td > 55.95< / td > < td > 62.23< / 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 > 81.96< / td > < td > 56.63< / td > < td > 62.90< / 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 > 79.41< / td > < td > 51.54< / td > < td > 55.63< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2006.07733" target = "_blank" rel = "noopener noreferrer" > BYOL< / a > < / td > < td > selfsup/byol/r50_bs4096_ep200.py< / td > < td > default< / td > < td > 80.95< / td > < td > 51.87< / td > < td > 56.53< / td > < / tr > < / tbody > < / table >
2020-08-12 16:06:20 +08:00
### COCO2017 Object Detection
**Note**
* This benchmark follows the evluation protocols set up by MoCo.
* Config: `benchmarks/detection/configs/coco_R_50_C4_2x_moco.yaml` .
* Please follow [here ](GETTING_STARTED.md#voc0712--coco17-object-detection ) to run the evaluation.
< table > < thead > < tr > < th rowspan = "2" > Method< / th > < th rowspan = "2" > Config< / th > < th rowspan = "2" > Remarks< / th > < th colspan = "6" > COCO2017< / th > < / tr > < tr > < td > AP50(Box)< / td > < td > AP(Box)< / td > < td > AP75(Box)< / td > < td > AP50(Mask)< / td > < td > AP(Mask)< / td > < td > AP75(Mask)< / 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 > 59.9< / td > < td > 40.0< / td > < td > 43.1< / td > < td > 56.5< / td > < td > 34.7< / td > < td > 36.9< / td > < / tr > < tr > < td > Random< / td > < td > -< / td > < td > kaiming< / td > < td > 54.6< / td > < td > 35.6< / td > < td > 38.2< / td > < td > 51.5< / td > < td > 31.4< / td > < td > 33.5< / 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 > 59.6< / td > < td > 40.0< / td > < td > 43.5< / td > < td > 56.5< / td > < td > 35.0< / td > < td > 37.3< / 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 > 59.3< / td > < td > 40.0< / td > < td > 43.6< / td > < td > 56.0< / td > < td > 34.9< / td > < td > 37.4< / 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 > 59.0< / td > < td > 39.4< / td > < td > 42.8< / td > < td > 55.9< / td > < td > 34.5< / td > < td > 36.6< / 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 > 60.5< / td > < td > 40.9< / td > < td > 44.2< / td > < td > 57.1< / td > < td > 35.5< / td > < td > 37.7< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2003.04297" > MoCo v2< / a > < / td > < td > selfsup/moco/r50_v2.py< / td > < td > default< / td > < td > 60.7< / td > < td > 40.9< / td > < td > 44.2< / td > < td > 57.2< / td > < td > 35.5< / td > < td > 37.9< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2002.05709" > SimCLR< / a > < / td > < td > selfsup/simclr/r50_bs256_ep200.py< / td > < td > default< / td > < td > 59.1< / td > < td > 39.6< / td > < td > 42.9< / td > < td > 55.9< / td > < td > 34.6< / td > < td > 37.1< / td > < / tr > < tr > < td > < a href = "https://arxiv.org/abs/2006.07733" > 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 >
