MMPose V0.10.0 Release

Highlights

1. Support more human pose estimation methods.
   • UDP
2. Support pose tracking.
3. Support multi-batch inference.
4. Add some useful tools, including analyze_logs, get_flops, print_config.
5. Support more backbone networks.
   • ResNest
   • VGG

New Features

• Support UDP (#353, #371, #402)
• Support multi-batch inference (#390)
• Support MHP dataset (#386)
• Support pose tracking demo (#380)
• Support MPII-TRB demo (#372)
• Support MobileNet for hand pose estimation (#377)
• Support ResNest backbone (#370)
• Support VGG backbone (#370)
• Add some useful tools, including analyze_logs, get_flops, print_config (#324)

Bug Fixes

• Fix bugs in pck evaluation (#328)
• Fix model download links in README (#396, #397)
• Fix CrowdPose annotations and update benchmarks (#384)
• Fix modelzoo stat (#354, #360, #362)
• Fix config files for AIC datasets (#340)

Breaking Changes

• Rename image_thr to det_bbox_thr for top-down methods.

Improvements

• Organize the readme files (#398, #399, #400)
• Check linting for markdown (#379)
• Add faq.md (#350)
• Remove PyTorch 1.4 in CI (#338)
• Add pypi badge in readme (#329)

MMPose V0.9.0 Release

Highlights

1. Support more human pose estimation methods.
   • MSPN
   • RSN
2. Support video pose estimation datasets.
   • sub-JHMDB
3. Support Onnx model conversion.

New Features

• Support MSPN (#278)
• Support RSN (#221, #318)
• Support new post-processing method for MSPN & RSN (#288)
• Support sub-JHMDB dataset (#292)
• Support urls for pre-trained models in config files (#232)
• Support Onnx (#305)

Bug Fixes

• Fix model download links in README (#255, #315)

Breaking Changes

• post_process=True|False and unbiased_decoding=True|False are deprecated, use post_process=None|default|unbiased etc. instead (#288)

Improvements

• Enrich the model zoo (#256, #320)
• Set the default map_location as 'cpu' to reduce gpu memory cost (#227)
• Support return heatmaps and backbone features for bottom-up models (#229)
• Upgrade mmcv maximum & minimum version (#269, #313)
• Automatically add modelzoo statistics to readthedocs (#252)
• Fix Pylint issues (#258, #259, #260, #262, #265, #267, #268, #270, #271, #272, #273, #275, #276, #283, #285, #293, #294, #295)
• Improve README (#226, #257, #264, #280, #296)
• Support PyTorch 1.7 in CI (#274)
• Add docs/tutorials for running demos (#263)

MMPose V0.8.0 Release

Highlights

1. Support more human pose estimation datasets.
   • CrowdPose
   • PoseTrack18
2. Support more 2D hand keypoint estimation datasets.
   • InterHand2.6
3. Support adversarial training for 3D human shape recovery.
4. Support multi-stage losses.
5. Support mpii demo.

New Features

• Support CrowdPose dataset (#195).
• Support PoseTrack18 dataset (#220).
• Support InterHand2.6 dataset (#202).
• Support adversarial training for 3D human shape recovery (#192).
• Support multi-stage losses (#204).

Bug Fixes

• Fix config files (#190)

Improvements

• Add mpii demo (#216)
• Improve README (#181, #183, #208)
• Support return heatmaps and backbone features (#196, #212)
• Support different return formats of mmdetection models (#217)

MMPose V0.7.0 Release

Highlights

1. Support HMR for 3D human shape recovery.
2. Support WholeBody human pose estimation.
   • COCO-WholeBody
3. Support more 2D hand keypoint estimation datasets.
   • Frei-hand
   • CMU Panoptic HandDB
4. Add more popular backbones & enrich the modelzoo.
   • ShuffleNetv2
5. Support hand demo and whole-body demo.

New Features

• Support HMR for 3D human shape recovery (#157, #160, #161, #162)
• Support COCO-WholeBody dataset (#133)
• Support Frei-hand dataset (#125)
• Support CMU Panoptic HandDB dataset (#144)
• Support H36M dataset (#159)
• Support ShuffleNetv2 (#139)
• Support saving best models based on key indicator (#127)

Bug Fixes

• Fix typos in docs (#121)
• Fix assertion (#142)

Improvements

• Add tools to transform .mat format to .json format (#126)
• Add hand demo (#115)
• Add whole-body demo (#163)
• Reuse mmcv utility function and update version files (#135, #137)
• Enrich the modelzoo (#147, #169)
• Improve docs (#174, #175, #178)
• Improve README (#176)
• Improve version.py (#173)

MMPose V0.6.0 Release

Highlights

1. Add popular backbones & enrich the modelzoo.

   • ResNext
   • SEResNet
   • ResNetV1D
   • MobileNetv2
   • ShuffleNetv1
   • CPM (Convolutional Pose Machine)

2. Add popular datasets:

   • AIChallenger
   • MPII
   • MPII-TRB
   • OCHuman

3. Support 2d hand keypoint estimation.

   • OneHand10K

4. Support bottom-up inference.

New Features

• Support OneHand10K dataset (#52).
• Support MPII dataset (#55).
• Support MPII-TRB dataset (#19, #47, #48).
• Support OCHuman dataset (#70).
• Support AIChallenger dataset (#87).
• Support multiple backbones (#26).
• Support CPM model (#56).

Bug Fixes

• Fix configs for MPII & MPII-TRB datasets (#93).
• Fix the bug of missing test_pipeline in configs (#14).
• Fix typos (#27, #28, #50, #53, #63).

Improvements

• Update benchmark (#93).
• Add Dockerfile (#44).
• Improve unittest coverage and minor fix (#18).
• Support CPUs for train/val/demo (#34).
• Support bottom-up demo (#69).
• Add tools to publish model (#62).
• Enrich the modelzoo (#64, #68, #82).