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* update

* [Fix] Fix HRFormer log link

* [Feature] Add Application 'Just dance' (#2528)

* [Docs] Add advanced tutorial of implement new model. (#2539)

* [Doc] Update img (#2541)

* [Feature] Support MotionBERT (#2482)

* [Fix] Fix demo scripts (#2542)

* [Fix] Fix Pose3dInferencer keypoint shape bug (#2543)

* [Enhance] Add notifications when saving visualization results (#2545)

* [Fix] MotionBERT training and flip-test (#2548)

* [Docs] Enhance docs (#2555)

* [Docs] Fix links in doc (#2557)

* [Docs] add details (#2558)

* [Refactor] 3d human pose demo (#2554)

* [Docs] Update MotionBERT docs (#2559)

* [Refactor] Update the arguments of 3d inferencer to align with the demo script (#2561)

* [Enhance] Combined dataset supports custom sampling ratio (#2562)

* [Docs] Add MultiSourceSampler docs (#2563)

* [Doc] Refine docs (#2564)

* [Feature][MMSIG] Add UniFormer Pose Estimation to Projects folder (#2501)

* [Fix] Check the compatibility of inferencer's input/output  (#2567)

* [Fix]Fix 3d visualization (#2565)

* [Feature] Add bear example in just dance (#2568)

* [Doc] Add example and openxlab link for just dance (#2571)

* [Fix] Configs' paths of VideoPose3d (#2572)

* [Docs] update docs (#2573)

* [Fix] Fix new config bug in train.py (#2575)

* [Fix] Configs' of MotionBERT (#2574)

* [Enhance] Normalization option in 3d human pose demo and inferencer (#2576)

* [Fix] Fix the incorrect labels for training vis_head with combined datasets (#2550)

* [Enhance] Enhance 3dpose demo and docs (#2578)

* [Docs] Enhance Codecs documents (#2580)

* [Feature] Add DWPose distilled WholeBody RTMPose models (#2581)

* [Docs] Add deployment docs (#2582)

* [Fix] Refine 3dpose (#2583)

* [Fix] Fix config typo in rtmpose-x (#2585)

* [Fix] Fix 3d inferencer (#2593)

* [Feature] Add a simple visualize api (#2596)

* [Feature][MMSIG] Support badcase analyze in test (#2584)

* [Fix] fix bug in flip_bbox with xyxy format (#2598)

* [Feature] Support ubody dataset (2d keypoints) (#2588)

* [Fix] Fix visualization bug in 3d pose (#2594)

* [Fix] Remove use-multi-frames option (#2601)

* [Enhance] Update demos (#2602)

* [Enhance] wholebody support  openpose style visualization (#2609)

* [Docs] Documentation regarding 3d pose (#2599)

* [CodeCamp2023-533] Migration Deepfashion topdown heatmap algorithms to 1.x (#2597)

* [Fix] fix badcase hook (#2616)

* [Fix] Update dataset mim downloading source to OpenXLab (#2614)

* [Docs] Update docs structure (#2617)

* [Docs] Refine Docs (#2619)

* [Fix] Fix numpy error (#2626)

* [Docs] Update error info and docs (#2624)

* [Fix] Fix inferencer argument name (#2627)

* [Fix] fix links for coco+aic hrnet (#2630)

* [Fix] fix a bug when visualize keypoint indices (#2631)

* [Docs] Update rtmpose docs (#2642)

* [Docs] update README.md (#2647)

* [Docs] Add onnx of RTMPose models (#2656)

* [Docs] Fix mmengine link (#2655)

* [Docs] Update QR code (#2653)

* [Feature] Add DWPose (#2643)

* [Refactor] Reorganize distillers (#2658)

* [CodeCamp2023-259]Document Writing: Advanced Tutorial - Custom Data Augmentation (#2605)

* [Docs] Fix installation docs(#2668)

* [Fix] Fix expired links in README (#2673)

* [Feature] Support multi-dataset evaluation (#2674)

* [Refactor] Specify labels to pack in codecs (#2659)

* [Refactor] update mapping tables (#2676)

* [Fix] fix link (#2677)

* [Enhance] Enable CocoMetric to get ann_file from MessageHub (#2678)

* [Fix] fix vitpose pretrained ckpts (#2687)

* [Refactor] Refactor YOLOX-Pose into mmpose core package (#2620)

* [Fix] Fix typo in COCOMetric(#2691)

* [Fix] Fix bug raised by changing bbox_center to input_center (#2693)

* [Feature] Surpport EDPose for inference(#2688)

* [Refactor] Internet for 3d hand pose estimation (#2632)

* [Fix] Change test batch_size of edpose to 1 (#2701)

* [Docs] Add OpenXLab Badge (#2698)

* [Doc] fix inferencer doc (#2702)

* [Docs] Refine dataset config tutorial (#2707)

* [Fix] modify yoloxpose test settings (#2706)

* [Fix] add compatibility for argument `return_datasample` (#2708)

* [Feature] Support ubody3d dataset (#2699)

* [Fix] Fix 3d inferencer (#2709)

* [Fix] Move ubody3d dataset to wholebody3d (#2712)

* [Refactor] Refactor config and dataset file structures (#2711)

* [Fix] give more clues when loading img failed (#2714)

* [Feature] Add demo script for 3d hand pose  (#2710)

* [Fix] Fix Internet demo (#2717)

* [codecamp: mmpose-315] 300W-LP data set support (#2716)

* [Fix] Fix the typo in YOLOX-Pose (#2719)

* [Feature] Add detectors trained on humanart (#2724)

* [Feature] Add RTMPose-Wholebody (#2721)

* [Doc] Fix github action badge in README (#2727)

* [Fix] Fix bug of dwpose (#2728)

* [Feature] Support hand3d inferencer (#2729)

* [Fix] Fix new config of RTMW (#2731)

* [Fix] Align visualization color of 3d demo (#2734)

* [Fix] Refine h36m data loading and add head_size to PackPoseInputs (#2735)

* [Refactor] Align test accuracy for AE (#2737)

* [Refactor] Separate evaluation mappings from KeypointConverter (#2738)

* [Fix] MotionbertLabel codec (#2739)

* [Fix] Fix mask shape (#2740)

* [Feature] Add training datasets of RTMW (#2743)

* [Doc] update RTMPose README (#2744)

* [Fix] skip warnings in demo (#2746)

* Bump 1.2 (#2748)

* add comments in dekr configs (#2751)

---------

Co-authored-by: Peng Lu <penglu2097@gmail.com>
Co-authored-by: Yifan Lareina WU <mhsj16lareina@gmail.com>
Co-authored-by: Xin Li <7219519+xin-li-67@users.noreply.github.com>
Co-authored-by: Indigo6 <40358785+Indigo6@users.noreply.github.com>
Co-authored-by: 谢昕辰 <xiexinch@outlook.com>
Co-authored-by: tpoisonooo <khj.application@aliyun.com>
Co-authored-by: zhengjie.xu <jerryxuzhengjie@gmail.com>
Co-authored-by: Mesopotamia <54797851+yzd-v@users.noreply.github.com>
Co-authored-by: chaodyna <li0331_1@163.com>
Co-authored-by: lwttttt <85999869+lwttttt@users.noreply.github.com>
Co-authored-by: Kanji Yomoda <Kanji.yy@gmail.com>
Co-authored-by: LiuYi-Up <73060646+LiuYi-Up@users.noreply.github.com>
Co-authored-by: ZhaoQiiii <102809799+ZhaoQiiii@users.noreply.github.com>
Co-authored-by: Yang-ChangHui <71805205+Yang-Changhui@users.noreply.github.com>
Co-authored-by: Xuan Ju <89566272+juxuan27@users.noreply.github.com>
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4 changes: 2 additions & 2 deletions .github/workflows/merge_stage_test.yml
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Expand Up @@ -208,17 +208,17 @@ jobs:
- name: Install mmpose dependencies
run: |
python -m pip install -U numpy
python -m pip install --upgrade pip setuptools wheel
python -m pip install git+https://github.com/open-mmlab/mmengine.git@main
python -m pip install -U openmim
mim install 'mmcv >= 2.0.0'
python -m pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
mim install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
python -m pip install -r requirements/tests.txt
python -m pip install -r requirements/runtime.txt
python -m pip install -r requirements/albu.txt
python -m pip install -r requirements/poseval.txt
- name: Build and install
run: |
python -m pip install --upgrade pip setuptools wheel
python -m pip install -e . -v
- name: Run unittests and generate coverage report
run: |
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4 changes: 2 additions & 2 deletions .github/workflows/pr_stage_test.yml
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Expand Up @@ -178,16 +178,16 @@ jobs:
- name: Install mmpose dependencies
run: |
python -m pip install -U numpy
python -m pip install --upgrade pip setuptools wheel
python -m pip install git+https://github.com/open-mmlab/mmengine.git@main
python -m pip install -U openmim
mim install 'mmcv >= 2.0.0'
python -m pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
mim install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
python -m pip install -r requirements/tests.txt
python -m pip install -r requirements/albu.txt
python -m pip install -r requirements/poseval.txt
- name: Build and install
run: |
python -m pip install --upgrade pip setuptools wheel
python -m pip install -e . -v
- name: Run unittests and generate coverage report
run: |
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6 changes: 4 additions & 2 deletions .readthedocs.yml
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Expand Up @@ -2,9 +2,11 @@ version: 2

formats:
- epub

build:
os: ubuntu-22.04
tools:
python: "3.8"
python:
version: 3.7
install:
- requirements: requirements/docs.txt
- requirements: requirements/readthedocs.txt
7 changes: 7 additions & 0 deletions LICENSES.md
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@@ -0,0 +1,7 @@
# Licenses for special algorithms

In this file, we list the algorithms with other licenses instead of Apache 2.0. Users should be careful about adopting these algorithms in any commercial matters.

| Algorithm | Files | License |
| :-------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------: |
| EDPose | [mmpose/models/heads/transformer_heads/edpose_head.py](https://github.com/open-mmlab/mmpose/blob/main/mmpose/models/heads/transformer_heads/edpose_head.py) | IDEA License 1.0 |
107 changes: 44 additions & 63 deletions README.md
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Expand Up @@ -19,12 +19,13 @@
<div>&nbsp;</div>

[![Documentation](https://readthedocs.org/projects/mmpose/badge/?version=latest)](https://mmpose.readthedocs.io/en/latest/?badge=latest)
[![actions](https://github.com/open-mmlab/mmpose/workflows/build/badge.svg)](https://github.com/open-mmlab/mmpose/actions)
[![actions](https://github.com/open-mmlab/mmpose/workflows/merge_stage_test/badge.svg)](https://github.com/open-mmlab/mmpose/actions)
[![codecov](https://codecov.io/gh/open-mmlab/mmpose/branch/latest/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmpose)
[![PyPI](https://img.shields.io/pypi/v/mmpose)](https://pypi.org/project/mmpose/)
[![LICENSE](https://img.shields.io/github/license/open-mmlab/mmpose.svg)](https://github.com/open-mmlab/mmpose/blob/main/LICENSE)
[![Average time to resolve an issue](https://isitmaintained.com/badge/resolution/open-mmlab/mmpose.svg)](https://github.com/open-mmlab/mmpose/issues)
[![Percentage of issues still open](https://isitmaintained.com/badge/open/open-mmlab/mmpose.svg)](https://github.com/open-mmlab/mmpose/issues)
[![Open in OpenXLab](https://cdn-static.openxlab.org.cn/app-center/openxlab_demo.svg)](https://openxlab.org.cn/apps?search=mmpose)

[📘Documentation](https://mmpose.readthedocs.io/en/latest/) |
[🛠️Installation](https://mmpose.readthedocs.io/en/latest/installation.html) |
Expand Down Expand Up @@ -97,76 +98,51 @@ https://user-images.githubusercontent.com/15977946/124654387-0fd3c500-ded1-11eb-

## What's New

- We are glad to support 3 new datasets:
- (CVPR 2023) [Human-Art](https://github.com/IDEA-Research/HumanArt)
- (CVPR 2022) [Animal Kingdom](https://github.com/sutdcv/Animal-Kingdom)
- (AAAI 2020) [LaPa](https://github.com/JDAI-CV/lapa-dataset/)
- We have added support for two new datasets:

![image](https://github.com/open-mmlab/mmpose/assets/13503330/c9171dbb-7e7a-4c39-98e3-c92932182efb)
- (CVPR 2023) [UBody](https://mmpose.readthedocs.io/zh_CN/latest/model_zoo_papers/datasets.html#ubody-cvpr-2023)
- [300W-LP](https://github.com/open-mmlab/mmpose/tree/main/configs/face_2d_keypoint/topdown_heatmap/300wlp)

- Welcome to [*projects of MMPose*](/projects/README.md), where you can access to the latest features of MMPose, and share your ideas and codes with the community at once. Contribution to MMPose will be simple and smooth:
- Support for four new algorithms:

- Provide an easy and agile way to integrate algorithms, features and applications into MMPose
- Allow flexible code structure and style; only need a short code review process
- Build individual projects with full power of MMPose but not bound up with heavy frameworks
- Checkout new projects:
- (ICCV 2023) [MotionBERT](https://github.com/open-mmlab/mmpose/tree/main/configs/body_3d_keypoint/motionbert)
- (ICCVW 2023) [DWPose](https://github.com/open-mmlab/mmpose/tree/main/configs/wholebody_2d_keypoint/dwpose)
- (ICLR 2023) [EDPose](https://mmpose.readthedocs.io/zh_CN/latest/model_zoo/body_2d_keypoint.html#edpose-edpose-on-coco)
- (ICLR 2022) [Uniformer](https://github.com/open-mmlab/mmpose/tree/main/projects/uniformer)

- Released the first whole-body pose estimation model, RTMW, with accuracy exceeding 70 AP on COCO-Wholebody. For details, refer to [RTMPose](/projects/rtmpose/). [Try it now!](https://openxlab.org.cn/apps/detail/mmpose/RTMPose)

![rtmw](https://github.com/open-mmlab/mmpose/assets/13503330/635c4618-c459-45e8-84a5-eb68cf338d00)

- Welcome to use the [*MMPose project*](/projects/README.md). Here, you can discover the latest features and algorithms in MMPose and quickly share your ideas and code implementations with the community. Adding new features to MMPose has become smoother:

- Provides a simple and fast way to add new algorithms, features, and applications to MMPose.
- More flexible code structure and style, fewer restrictions, and a shorter code review process.
- Utilize the powerful capabilities of MMPose in the form of independent projects without being constrained by the code framework.
- Newly added projects include:
- [RTMPose](/projects/rtmpose/)
- [YOLOX-Pose](/projects/yolox_pose/)
- [MMPose4AIGC](/projects/mmpose4aigc/)
- [Simple Keypoints](/projects/skps/)
- Become a contributors and make MMPose greater. Start your journey from the [example project](/projects/example_project/)
- [Just Dance](/projects/just_dance/)
- [Uniformer](/projects/uniformer/)
- Start your journey as an MMPose contributor with a simple [example project](/projects/example_project/), and let's build a better MMPose together!

<br/>

- 2023-07-04: MMPose [v1.1.0](https://github.com/open-mmlab/mmpose/releases/tag/v1.1.0) is officially released, with the main updates including:
- October 12, 2023: MMPose [v1.2.0](https://github.com/open-mmlab/mmpose/releases/tag/v1.2.0) has been officially released, with major updates including:

- Support new datasets: Human-Art, Animal Kingdom and LaPa.
- Support new config type that is more user-friendly and flexible.
- Improve RTMPose with better performance.
- Migrate 3D pose estimation models on h36m.
- Inference speedup and webcam inference with all demo scripts.
- Support for new datasets: UBody, 300W-LP.
- Support for new algorithms: MotionBERT, DWPose, EDPose, Uniformer.
- Migration of Associate Embedding, InterNet, YOLOX-Pose algorithms.
- Migration of the DeepFashion2 dataset.
- Support for Badcase visualization analysis, multi-dataset evaluation, and keypoint visibility prediction features.

Please refer to the [release notes](https://github.com/open-mmlab/mmpose/releases/tag/v1.1.0) for more updates brought by MMPose v1.1.0!
Please check the complete [release notes](https://github.com/open-mmlab/mmpose/releases/tag/v1.2.0) for more details on the updates brought by MMPose v1.2.0!

## 0.x / 1.x Migration

MMPose v1.0.0 is a major update, including many API and config file changes. Currently, a part of the algorithms have been migrated to v1.0.0, and the remaining algorithms will be completed in subsequent versions. We will show the migration progress in the following list.

<details close>
<summary><b>Migration Progress</b></summary>

| Algorithm | Status |
| :-------------------------------- | :---------: |
| MTUT (CVPR 2019) | |
| MSPN (ArXiv 2019) | done |
| InterNet (ECCV 2020) | |
| DEKR (CVPR 2021) | done |
| HigherHRNet (CVPR 2020) | |
| DeepPose (CVPR 2014) | done |
| RLE (ICCV 2021) | done |
| SoftWingloss (TIP 2021) | done |
| VideoPose3D (CVPR 2019) | done |
| Hourglass (ECCV 2016) | done |
| LiteHRNet (CVPR 2021) | done |
| AdaptiveWingloss (ICCV 2019) | done |
| SimpleBaseline2D (ECCV 2018) | done |
| PoseWarper (NeurIPS 2019) | |
| SimpleBaseline3D (ICCV 2017) | done |
| HMR (CVPR 2018) | |
| UDP (CVPR 2020) | done |
| VIPNAS (CVPR 2021) | done |
| Wingloss (CVPR 2018) | done |
| DarkPose (CVPR 2020) | done |
| Associative Embedding (NIPS 2017) | in progress |
| VoxelPose (ECCV 2020) | |
| RSN (ECCV 2020) | done |
| CID (CVPR 2022) | done |
| CPM (CVPR 2016) | done |
| HRNet (CVPR 2019) | done |
| HRNetv2 (TPAMI 2019) | done |
| SCNet (CVPR 2020) | done |

</details>
MMPose v1.0.0 is a major update, including many API and config file changes. Currently, a part of the algorithms have been migrated to v1.0.0, and the remaining algorithms will be completed in subsequent versions. We will show the migration progress in this [Roadmap](https://github.com/open-mmlab/mmpose/issues/2258).

If your algorithm has not been migrated, you can continue to use the [0.x branch](https://github.com/open-mmlab/mmpose/tree/0.x) and [old documentation](https://mmpose.readthedocs.io/en/0.x/).

Expand All @@ -186,6 +162,9 @@ We provided a series of tutorials about the basic usage of MMPose for new users:
- [Configs](https://mmpose.readthedocs.io/en/latest/user_guides/configs.html)
- [Prepare Datasets](https://mmpose.readthedocs.io/en/latest/user_guides/prepare_datasets.html)
- [Train and Test](https://mmpose.readthedocs.io/en/latest/user_guides/train_and_test.html)
- [Deployment](https://mmpose.readthedocs.io/en/latest/user_guides/how_to_deploy.html)
- [Model Analysis](https://mmpose.readthedocs.io/en/latest/user_guides/model_analysis.html)
- [Dataset Annotation and Preprocessing](https://mmpose.readthedocs.io/en/latest/user_guides/dataset_tools.html)

2. For developers who wish to develop based on MMPose:

Expand All @@ -194,10 +173,11 @@ We provided a series of tutorials about the basic usage of MMPose for new users:
- [Implement New Models](https://mmpose.readthedocs.io/en/latest/advanced_guides/implement_new_models.html)
- [Customize Datasets](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_datasets.html)
- [Customize Data Transforms](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_transforms.html)
- [Customize Evaluation](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_evaluation.html)
- [Customize Optimizer](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_optimizer.html)
- [Customize Logging](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_logging.html)
- [How to Deploy](https://mmpose.readthedocs.io/en/latest/advanced_guides/how_to_deploy.html)
- [Model Analysis](https://mmpose.readthedocs.io/en/latest/advanced_guides/model_analysis.html)
- [How to Deploy](https://mmpose.readthedocs.io/en/latest/user_guides/how_to_deploy.html)
- [Model Analysis](https://mmpose.readthedocs.io/en/latest/user_guides/model_analysis.html)
- [Migration Guide](https://mmpose.readthedocs.io/en/latest/migration.html)

3. For researchers and developers who are willing to contribute to MMPose:
Expand All @@ -213,7 +193,7 @@ We provided a series of tutorials about the basic usage of MMPose for new users:
Results and models are available in the **README.md** of each method's config directory.
A summary can be found in the [Model Zoo](https://mmpose.readthedocs.io/en/latest/model_zoo.html) page.

<details close>
<details open>
<summary><b>Supported algorithms:</b></summary>

- [x] [DeepPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#deeppose-cvpr-2014) (CVPR'2014)
Expand All @@ -231,7 +211,7 @@ A summary can be found in the [Model Zoo](https://mmpose.readthedocs.io/en/lates
- [x] [SCNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#scnet-cvpr-2020) (CVPR'2020)
- [ ] [HigherHRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#higherhrnet-cvpr-2020) (CVPR'2020)
- [x] [RSN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#rsn-eccv-2020) (ECCV'2020)
- [ ] [InterNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#internet-eccv-2020) (ECCV'2020)
- [x] [InterNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#internet-eccv-2020) (ECCV'2020)
- [ ] [VoxelPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#voxelpose-eccv-2020) (ECCV'2020)
- [x] [LiteHRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#litehrnet-cvpr-2021) (CVPR'2021)
- [x] [ViPNAS](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#vipnas-cvpr-2021) (CVPR'2021)
Expand All @@ -240,7 +220,7 @@ A summary can be found in the [Model Zoo](https://mmpose.readthedocs.io/en/lates

</details>

<details close>
<details open>
<summary><b>Supported techniques:</b></summary>

- [x] [FPN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#fpn-cvpr-2017) (CVPR'2017)
Expand All @@ -255,7 +235,7 @@ A summary can be found in the [Model Zoo](https://mmpose.readthedocs.io/en/lates

</details>

<details close>
<details open>
<summary><b>Supported datasets:</b></summary>

- [x] [AFLW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#aflw-iccvw-2011) \[[homepage](https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/aflw/)\] (ICCVW'2011)
Expand Down Expand Up @@ -291,10 +271,11 @@ A summary can be found in the [Model Zoo](https://mmpose.readthedocs.io/en/lates
- [x] [Horse-10](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#horse-10-wacv-2021) \[[homepage](http://www.mackenziemathislab.org/horse10)\] (WACV'2021)
- [x] [Human-Art](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#human-art-cvpr-2023) \[[homepage](https://idea-research.github.io/HumanArt/)\] (CVPR'2023)
- [x] [LaPa](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#lapa-aaai-2020) \[[homepage](https://github.com/JDAI-CV/lapa-dataset)\] (AAAI'2020)
- [x] [UBody](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ubody-cvpr-2023) \[[homepage](https://github.com/IDEA-Research/OSX)\] (CVPR'2023)

</details>

<details close>
<details open>
<summary><b>Supported backbones:</b></summary>

- [x] [AlexNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#alexnet-neurips-2012) (NeurIPS'2012)
Expand Down

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