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mmselfsup/docs/en/model_zoo.md

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Model Zoo

All models and part of benchmark results are recorded below.

Pre-trained models

Algorithm Config Download
BYOL byol_resnet50_8xb32-accum16-coslr-200e_in1k model | log
byol_resnet50_8xb32-accum16-coslr-300e_in1k model | log
DeepCLuster deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k model
DenseCL densecl_resnet50_8xb32-coslr-200e_in1k model | log
MoCo v2 mocov2_resnet50_8xb32-coslr-200e_in1k model | log
NPID npid_resnet50_8xb32-steplr-200e_in1k model | log
ODC odc_resnet50_8xb64-steplr-440e_in1k model
Relative Location relative-loc_resnet50_8xb64-steplr-70e_in1k model | log
Rotation Prediction rotation-pred_resnet50_8xb16-steplr-70e_in1k model | log
SimCLR simclr_resnet50_8xb32-coslr-200e_in1k model
SimSiam simsiam_resnet50_8xb32-coslr-100e_in1k model | log
simsiam_resnet50_8xb32-coslr-200e_in1k model | log
SwAV swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96 model | log

Remarks:

  • The training details are recorded in the config names.

  • You can click algorithm name to obtain more information.

Benchmarks

In following tables, we only displayed ImageNet Linear Evaluation, COCO17 Object Detection and PASCAL VOC12 Aug Segmentation, you can click algorithm name above to check the comprehensive benchmark results.

ImageNet Linear Evaluation

If not specified, we use linear evaluation setting from MoCo. Or the settings is mentioned in Remark.

Algorithm Config Remarks Top-1 (%)
BYOL byol_resnet50_8xb32-accum16-coslr-200e_in1k 67.68
DeepCLuster deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k.py 46.92
DenseCL densecl_resnet50_8xb32-coslr-200e_in1k 63.34
MoCo v2 mocov2_resnet50_8xb32-coslr-200e_in1k 67.56
NPID npid_resnet50_8xb32-steplr-200e_in1k 58.16
ODC odc_resnet50_8xb64-steplr-440e_in1k 53.42
Relative Location relative-loc_resnet50_8xb64-steplr-70e_in1k 39.65
Rotation Prediction rotation-pred_resnet50_8xb16-steplr-70e_in1k 44.35
SimCLR simclr_resnet50_8xb32-coslr-200e_in1k 58.92
SimSiam simsiam_resnet50_8xb32-coslr-100e_in1k SimSiam paper setting 68.20
simsiam_resnet50_8xb32-coslr-200e_in1k SimSiam paper setting 69.80
SwAV swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96 SwAV paper setting 70.55

COCO17 Object Detection

In COCO17 Object detection task, we choose the evluation protocol from MoCo, with Mask-RCNN architecture, the results below are trained with the same config.

Algorithm Config mAP (Box) mAP (Mask)
BYOL byol_resnet50_8xb32-accum16-coslr-200e_in1k 40.9 36.8
DenseCL densecl_resnet50_8xb32-coslr-200e_in1k
MoCo v2 mocov2_resnet50_8xb32-coslr-200e_in1k 40.2 36.1
NPID npid_resnet50_8xb32-steplr-200e_in1k
Relative Location relative-loc_resnet50_8xb64-steplr-70e_in1k 37.5 33.7
Rotation Prediction rotation-pred_resnet50_8xb16-steplr-70e_in1k 37.9 34.2
SimCLR simclr_resnet50_8xb32-coslr-200e_in1k 38.7 34.9
SimSiam simsiam_resnet50_8xb32-coslr-100e_in1k 38.6 34.6
simsiam_resnet50_8xb32-coslr-200e_in1k 38.8 34.9
SwAV swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96 40.2 36.3

Pascal VOC12 Aug Segmentation

In Pascal VOC12 Aug Segmentation task, we choose the evluation protocol from MMSeg, with FCN architecture, the results below are trained with the same config.

Algorithm Config mIOU
BYOL byol_resnet50_8xb32-accum16-coslr-200e_in1k 67.16
DeepCLuster deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k 59.69
DenseCL densecl_resnet50_8xb32-coslr-200e_in1k 69.47
MoCo v2 mocov2_resnet50_8xb32-coslr-200e_in1k 67.55
NPID npid_resnet50_8xb32-steplr-200e_in1k 65.45
ODC odc_resnet50_8xb64-steplr-440e_in1k 54.76
Relative Location relative-loc_resnet50_8xb64-steplr-70e_in1k 63.49
Rotation Prediction rotation-pred_resnet50_8xb16-steplr-70e_in1k 64.31
SimCLR simclr_resnet50_8xb32-coslr-200e_in1k 64.03
SimSiam simsiam_resnet50_8xb32-coslr-100e_in1k 48.35
simsiam_resnet50_8xb32-coslr-200e_in1k 46.27
SwAV swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96 63.73