Update MODEL_ZOO.md

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 # Model Zoo
 
-OpenSelfSup needs your contribution!
-Since we don't have sufficient GPUs to run these large-scale experiments, your contributions, including parameter studies, reproducing of results, implementing new methods, etc, are essential to make OpenSelfSup better. Your contribution will be recorded and recognized, top contributors will be included in the author list of OpenSelfSup!
+**OpenSelfSup needs your contribution!
+Since we don't have sufficient GPUs to run these large-scale experiments, your contributions, including parameter studies, reproducing of results, implementing new methods, etc, are essential to make OpenSelfSup better. Your contribution will be recorded in the below table, top contributors will be included in the author list of OpenSelfSup!**
 
 ## Pre-trained model download links and speed test.
 **Note**
-* The testing GPUs are NVIDIA Tesla V100.
+* If not specifically indicated, the testing GPUs are NVIDIA Tesla V100.
 * Experiments with the same batch size are directly comparable in speed.
+* The table records the implementors who implemented the methods (either by themselves or refactoring from other repos), and the experimenters who performed experiments and reproduced the results. The experimenters should be responsible for the evaluation results on all the benchmarks, and the implementors should be responsible for the implementation as well as the results; If the experimenter is not indicated, an implementator is the experimenter by default.
 
-<table><thead><tr><th>Method</th><th>Config</th><th>Remarks</th><th>Download link</th><th>Batch size</th><th>Epochs</th><th>Time per epoch</th></tr></thead><tbody>
+<table><thead><tr><th>Method (Implementator)</th><th>Config (Experimenter)</th><th>Remarks</th><th>Download link</th><th>Batch size</th><th>Epochs</th><th>Time per epoch</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><td>-</td><td>-</td><td>-</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><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>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><td>512</td><td>70</td><td>21min17s</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><td>128</td><td>70</td><td>49min58s</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><td>512</td><td>200</td><td>41min57s</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><td>256</td><td>200</td><td>20min5s</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> (<a href="https://github.com/Jiahao000">@Jiahao000</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><td>512</td><td>70</td><td>21min17s</td></tr>
+<tr><td><a href="https://arxiv.org/abs/1803.07728" target="_blank" rel="noopener noreferrer">Rotation-Pred</a> (<a href="https://github.com/XiaohangZhan">@XiaohangZhan</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><td>128</td><td>70</td><td>49min58s</td></tr>
+<tr><td><a href="https://arxiv.org/abs/1807.05520" target="_blank" rel="noopener noreferrer">DeepCluster</a> (<a href="https://github.com/XiaohangZhan">@XiaohangZhan</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><td>512</td><td>200</td><td>41min57s</td></tr>
+<tr><td><a href="https://arxiv.org/abs/1805.01978" target="_blank" rel="noopener noreferrer">NPID</a> (<a href="https://github.com/XiaohangZhan">@XiaohangZhan</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><td>256</td><td>200</td><td>20min5s</td></tr>
 <tr><td></td><td>selfsup/npid/r50_ensure_neg.py</td><td>ensure_neg=True</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><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><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><td>512</td><td>440</td><td>28min22s</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><td>256</td><td>200</td><td>22min58s</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/1ImO8A3uWbrTx21D1IqBDMUQvpN6wmv0d/view?usp=sharing" target="_blank" rel="noopener noreferrer">moco_r50_v2-e3b0c442.pth</a></td><td>256</td><td>200</td><td>55min43s</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><td>256</td><td>200</td><td>1h1min7s</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> (<a href="https://github.com/XiaohangZhan">@XiaohangZhan</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><td>512</td><td>440</td><td>28min22s</td></tr>
+<tr><td><a href="https://arxiv.org/abs/1911.05722" target="_blank" rel="noopener noreferrer">MoCo</a> (<a href="https://github.com/XiaohangZhan">@XiaohangZhan</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><td>256</td><td>200</td><td>22min58s</td></tr>
+<tr><td><a href="https://arxiv.org/abs/2003.04297" target="_blank" rel="noopener noreferrer">MoCo v2</a> (<a href="https://github.com/XiaohangZhan">@XiaohangZhan</a>)</td><td>selfsup/moco/r50_v2.py</td><td>default</td><td><a href="https://drive.google.com/file/d/1ImO8A3uWbrTx21D1IqBDMUQvpN6wmv0d/view?usp=sharing" target="_blank" rel="noopener noreferrer">moco_r50_v2-e3b0c442.pth</a></td><td>256</td><td>200</td><td>55min43s</td></tr>
+<tr><td><a href="https://arxiv.org/abs/2002.05709" target="_blank" rel="noopener noreferrer">SimCLR</a> (<a href="https://github.com/XiaohangZhan">@XiaohangZhan</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><td>256</td><td>200</td><td>1h1min7s</td></tr>
 <tr><td></td><td>selfsup/simclr/r50_bs256_ep200_mocov2_neck.py</td><td>-&gt; 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><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><a href="https://drive.google.com/file/d/1Whj3j5E3ShQj_VufjrJSzWiq1xcZZCXN/view?usp=sharing" target="_blank" rel="noopener noreferrer">byol_r50-e3b0c442.pth</a></td><td>4096</td><td>200</td><td>14min40s</td></tr>
+<tr><td><a href="https://arxiv.org/abs/2006.07733" target="_blank" rel="noopener noreferrer">BYOL</a> (<a href="https://github.com/XiaohangZhan">@XiaohangZhan</a>)</td><td>selfsup/byol/r50_bs4096_ep200.py (<a href="https://github.com/xieenze">@xieenze</a>)</td><td>default</td><td><a href="https://drive.google.com/file/d/1Whj3j5E3ShQj_VufjrJSzWiq1xcZZCXN/view?usp=sharing" target="_blank" rel="noopener noreferrer">byol_r50-e3b0c442.pth</a></td><td>4096</td><td>200</td><td>14min40s</td></tr>
 </tbody></table>
 
 ## Benchmarks