- Released with code refactor.
- Add 3 new self-supervised learning algorithms.
- Support benchmarks with MMDet and MMSeg.
- Add comprehensive documents.
- Merge redundant dataset files.
- Adapt to new version of MMCV and remove old version related codes.
- Inherit MMCV BaseModule.
- Optimize directory.
- Rename all config files.
- Add SwAV, SimSiam, DenseCL algorithms.
- Add t-SNE visualization tools.
- Support MMCV version fp16.
- More benchmarking results, including classification, detection and segmentation.
- Support some new datasets in downstream tasks.
- Launch MMDet and MMSeg training with MIM.
- Refactor README, getting_started, install, model_zoo files.
- Add data_prepare file.
- Add comprehensive tutorials.
- Support Mixed Precision Training
- Improvement of GaussianBlur doubles the training speed
- More benchmarking results
- Fix bugs in moco v2, now the results are reproducible.
- Fix bugs in byol.
- Mixed Precision Training
- Improvement of GaussianBlur doubles the training speed of MoCo V2, SimCLR, BYOL
- More benchmarking results, including Places, VOC, COCO
- Support BYOL
- Support semi-supervised benchmarks
- Fix hash id in publish_model.py
- Support BYOL.
- Separate train and test scripts in linear/semi evaluation.
- Support semi-supevised benchmarks: benchmarks/dist_train_semi.sh.
- Move benchmarks related configs into configs/benchmarks/.
- Provide benchmarking results and model download links.
- Support updating network every several iterations.
- Support LARS optimizer with nesterov.
- Support excluding specific parameters from LARS adaptation and weight decay required in SimCLR and BYOL.