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v0.19.0 (08/10/2021)

Highlights

  • Add models for Associative Embedding with Hourglass network backbone (#906, #955) @jin-s13, @luminxu

  • Support COCO-Wholebody-Face and COCO-Wholebody-Hand datasets (#813) @jin-s13, @innerlee, @luminxu

  • Upgrade dataset interface (#901, #924) @jin-s13, @innerlee, @ly015, @liqikai9

  • New style of documentation (#945) @ly015

New Features

  • Add models for Associative Embedding with Hourglass network backbone (#906, #955) @jin-s13, @luminxu

  • Support COCO-Wholebody-Face and COCO-Wholebody-Hand datasets (#813) @jin-s13, @innerlee, @luminxu

  • Add pseudo-labeling tool to generate COCO style keypoint annotations with given bounding boxes (#928) @soltkreig

  • New style of documentation (#945) @ly015

Bug Fixes

  • Fix segmentation parsing in Macaque dataset preprocessing (#948) @jin-s13

  • Fix dependencies that may lead to CI failure in downstream projects (#936, #953) @RangiLyu, @ly015

  • Fix keypoint order in Human3.6M dataset (#940) @ttxskk

  • Fix unstable image loading for Interhand2.6M (#913) @zengwang430521

Improvements

  • Upgrade dataset interface (#901, #924) @jin-s13, @innerlee, @ly015, @liqikai9

  • Improve demo usability and stability (#908, #934) @ly015

  • Standardize model metafile format (#941) @ly015

  • Support persistent_worker and several other arguments in configs (#946) @jin-s13

  • Use MMCV root model registry to enable cross-project module building (#935) @RangiLyu

  • Improve the document quality (#916, #909, #942, #913, #956) @jin-s13, @ly015, @bit-scientist, @zengwang430521

  • Improve pull request template (#952, #954) @ly015

Breaking Changes

  • Upgrade dataset interface (#901) @jin-s13, @innerlee, @ly015

v0.18.0 (01/09/2021)

Bug Fixes

  • Fix redundant model weight loading in pytorch-to-onnx conversion (#850) @ly015

  • Fix a bug in update_model_index.py that may cause pre-commit hook failure(#866) @ly015

  • Fix a bug in interhand_3d_head (#890) @zengwang430521

  • Fix pose tracking demo failure caused by out-of-date configs (#891)

Improvements

  • Add automatic benchmark regression tools (#849, #880, #885) @liqikai9, @ly015

  • Add copyright information and checking hook (#872)

  • Add PR template (#875) @ly015

  • Add citation information (#876) @ly015

  • Add python3.9 in CI (#877, #883) @ly015

  • Improve the quality of the documents (#845, #845, #848, #867, #870, #873, #896) @jin-s13, @ly015, @zhiqwang

v0.17.0 (06/08/2021)

Highlights

  1. Support “Lite-HRNet: A Lightweight High-Resolution Network” CVPR’2021 (#733,#800) @jin-s13

  2. Add 3d body mesh demo (#771) @zengwang430521

  3. Add Chinese documentation (#787, #798, #799, #802, #804, #805, #815, #816, #817, #819, #839) @ly015, @luminxu, @jin-s13, @liqikai9, @zengwang430521

  4. Add Colab Tutorial (#834) @ly015

New Features

Bug Fixes

  • Fix mpii pckh@0.1 index (#773) @jin-s13

  • Fix multi-node distributed test (#818) @ly015

  • Fix docstring and init_weights error of ShuffleNetV1 (#814) @Junjun2016

  • Fix imshow_bbox error when input bboxes is empty (#796) @ly015

  • Fix model zoo doc generation (#778) @ly015

  • Fix typo (#767), (#780, #782) @ly015, @jin-s13

Breaking Changes

  • Use MMCV EvalHook (#686) @ly015

Improvements

  • Add pytest.ini and fix docstring (#812) @jin-s13

  • Update MSELoss (#829) @Ezra-Yu

  • Move process_mmdet_results into inference.py (#831) @ly015

  • Update resource limit (#783) @jin-s13

  • Use COCO 2D pose model in 3D demo examples (#785) @ly015

  • Change model zoo titles in the doc from center-aligned to left-aligned (#792, #797) @ly015

  • Support MIM (#706, #794) @ly015

  • Update out-of-date configs (#827) @jin-s13

  • Remove opencv-python-headless dependency by albumentations (#833) @ly015

  • Update QQ QR code in README_CN.md (#832) @ly015

v0.16.0 (02/07/2021)

Highlights

  1. Support “ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search” CVPR’2021 (#742,#755).

  2. Support MPI-INF-3DHP dataset (#683,#746,#751).

  3. Add webcam demo tool (#729)

  4. Add 3d body and hand pose estimation demo (#704, #727).

New Features

Bug Fixes

Breaking Changes

  • Switch to MMCV MODEL_REGISTRY (#669)

Improvements

  • Refactor MeshMixDataset (#752)

  • Rename ‘GaussianHeatMap’ to ‘GaussianHeatmap’ (#745)

  • Update out-of-date configs (#734)

  • Improve compatibility for breaking changes (#731)

  • Enable to control radius and thickness in visualization (#722)

  • Add regex dependency (#720)

v0.15.0 (02/06/2021)

Highlights

  1. Support 3d video pose estimation (VideoPose3D).

  2. Support 3d hand pose estimation (InterNet).

  3. Improve presentation of modelzoo.

New Features

  • Support “InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image” (ECCV‘20) (#624)

  • Support “3D human pose estimation in video with temporal convolutions and semi-supervised training” (CVPR’19) (#602, #681)

  • Support 3d pose estimation demo (#653, #670)

  • Support bottom-up whole-body pose estimation (#689)

  • Support mmcli (#634)

Bug Fixes

Breaking Changes

  • Reorganize configs by tasks, algorithms, datasets, and techniques (#647)

  • Rename heads and detectors (#667)

Improvements

  • Add radius and thickness parameters in visualization (#638)

  • Add trans_prob parameter in TopDownRandomTranslation (#650)

  • Switch to MMCV MODEL_REGISTRY (#669)

  • Update dependencies (#674, #676)

v0.14.0 (06/05/2021)

Highlights

  1. Support animal pose estimation with 7 popular datasets.

  2. Support “A simple yet effective baseline for 3d human pose estimation” (ICCV’17).

New Features

  • Support “A simple yet effective baseline for 3d human pose estimation” (ICCV’17) (#554,#558,#566,#570,#589)

  • Support animal pose estimation (#559,#561,#563,#571,#603,#605)

  • Support Horse-10 dataset (#561), MacaquePose dataset (#561), Vinegar Fly dataset (#561), Desert Locust dataset (#561), Grevy’s Zebra dataset (#561), ATRW dataset (#571), and Animal-Pose dataset (#603)

  • Support bottom-up pose tracking demo (#574)

  • Support FP16 training (#584,#616,#626)

  • Support NMS for bottom-up (#609)

Bug Fixes

  • Fix bugs in the top-down demo, when there are no people in the images (#569).

  • Fix the links in the doc (#612)

Improvements

v0.13.0 (31/03/2021)

Highlights

  1. Support Wingloss.

  2. Support RHD hand dataset.

New Features

  • Support Wingloss (#482)

  • Support RHD hand dataset (#523, #551)

  • Support Human3.6m dataset for 3d keypoint detection (#518, #527)

  • Support TCN model for 3d keypoint detection (#521, #522)

  • Support Interhand3D model for 3d hand detection (#536)

  • Support Multi-task detector (#480)

Bug Fixes

  • Fix PCKh@0.1 calculation (#516)

  • Fix unittest (#529)

  • Fix circular importing (#542)

  • Fix bugs in bottom-up keypoint score (#548)

Improvements

v0.12.0 (28/02/2021)

Highlights

  1. Support DeepPose algorithm.

New Features

  • Support DeepPose algorithm (#446, #461)

  • Support interhand3d dataset (#468)

  • Support Albumentation pipeline (#469)

  • Support PhotometricDistortion pipeline (#485)

  • Set seed option for training (#493)

  • Add demos for face keypoint detection (#502)

Bug Fixes

  • Change channel order according to configs (#504)

  • Fix num_factors in UDP encoding (#495)

  • Fix configs (#456)

Breaking Changes

  • Refactor configs for wholebody pose estimation (#487, #491)

  • Rename decode function for heads (#481)

Improvements

v0.11.0 (31/01/2021)

Highlights

  1. Support fashion landmark detection.

  2. Support face keypoint detection.

  3. Support pose tracking with MMTracking.

New Features

  • Support fashion landmark detection (DeepFashion) (#413)

  • Support face keypoint detection (300W, AFLW, COFW, WFLW) (#367)

  • Support pose tracking demo with MMTracking (#427)

  • Support face demo (#443)

  • Support AIC dataset for bottom-up methods (#438, #449)

Bug Fixes

  • Fix multi-batch training (#434)

  • Fix sigmas in AIC dataset (#441)

  • Fix config file (#420)

Breaking Changes

  • Refactor Heads (#382)

Improvements

v0.10.0 (31/12/2020)

Highlights

  1. Support more human pose estimation methods.

  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.

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)

v0.9.0 (30/11/2020)

Highlights

  1. Support more human pose estimation methods.

  2. Support video pose estimation datasets.

  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

v0.8.0 (31/10/2020)

Highlights

  1. Support more human pose estimation datasets.

  2. Support more 2D hand keypoint estimation datasets.

  3. Support adversarial training for 3D human shape recovery.

  4. Support multi-stage losses.

  5. Support mpii demo.

New Features

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)

v0.7.0 (30/9/2020)

Highlights

  1. Support HMR for 3D human shape recovery.

  2. Support WholeBody human pose estimation.

  3. Support more 2D hand keypoint estimation datasets.

  4. Add more popular backbones & enrich the modelzoo

    • ShuffleNetv2

  5. Support hand demo and whole-body demo.

New Features

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)

v0.6.0 (31/8/2020)

Highlights

  1. Add more popular backbones & enrich the modelzoo

    • ResNext

    • SEResNet

    • ResNetV1D

    • MobileNetv2

    • ShuffleNetv1

    • CPM (Convolutional Pose Machine)

  2. Add more popular datasets:

  3. Support 2d hand keypoint estimation.

  4. Support bottom-up inference.

New Features

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)

v0.5.0 (21/7/2020)

Highlights

  • MMPose is released.

Main Features

  • Support both top-down and bottom-up pose estimation approaches.

  • Achieve higher training efficiency and higher accuracy than other popular codebases (e.g. AlphaPose, HRNet)

  • Support various backbone models: ResNet, HRNet, SCNet, Houglass and HigherHRNet.

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