Xrmocap

Highlights

- Add [mview_mperson_end2end_estimator](https://github.com/openxrlab/xrmocap/blob/main/xrmocap/core/estimation/mview_mperson_end2end_estimator.py) for learning-based method.
- Add SMPLX support and allow smpl_data initiation in [mview_sperson_smpl_estimator](https://github.com/openxrlab/xrmocap/blob/main/xrmocap/core/estimation/mview_sperson_smpl_estimator.py).
- Add multiple optimizers, detailed joint weights and priors, grad clipping for better SMPLify results.
- Add [mediapipe_estimator](https://github.com/openxrlab/xrmocap/blob/main/xrmocap/human_perception/keypoints_estimation/mediapipe_estimator.py) for human keypoints2d perception.

New Features

- Add `mview_mperson_end2end_estimator`, performing MvP estimation on customized data.
- Add `mediapipe_estimator`, another alternative human keypoints2d perception method like `mmpose_top_down_estimator`.
- Add `RemoveDuplicate` keypoints3d optimizer to remove duplicate MvP keypoints3d predictions.

Refactors

- Refactor `mview_sperson_smpl_estimator`, compatible with SMPLX.
- Refactor `SMPLify`, add grad clipping, joint angle priors, loss-parameter mapping, per-parameter optimizers, and body part weights.
- Refactor evaluation for learning-based methods.

Documentations

- Update download links for aliyun resources.
- Add documents for end2end estimator.
- Update tutorials for Shelf_50 demo.

CICD

- Fix linting error caused by flake8.

Bug Fixes

- Fix joint angle limits for shoulder prior.
- Fix device error for `betas` initiation.
- Fix file error for saving keypoints3d predicted by multiple GPUs evaluation.

Highlights

- Add [4D Association Graph](http://www.liuyebin.com/4dassociation/), the first Python implementation to reproduce this algorithm
- Add Multi-view multi-person top-down smpl estimation
- Add reprojection error point selector

New Features

- Add [4D Association Graph](http://www.liuyebin.com/4dassociation/), the first Python implementation to reproduce this algorithm
- Add Multi-view multi-person top-down smpl estimation
- Add structures for mview mperson kps3d/smpl estimator
- Add reprojection error point selector

Refactors

- Refactor Deformable and ProjAttn for MvP

Documentations

- Add readthedocs
- Add shape-aware 3d pose optim doc
- Update docs and tutorials for MvP training and evaluation
- Update docs and benchmark for MVPose and MVPose tracking
- Update docs for single person in getting started
- Add LICENSE note
- Add S-Lab license
- Fix outdata URL, and advices for docs

CICD

- Add some github actions for issue management
- Fix github workflow build job won't fail when pytest fails
- Remove secrets in build CI

Bug Fixes

- Fix SMPL(X/XD)Data
- Fix mistakes for mview sperson
- Fix bugs in MvP training

Highlights

- Support [HuMMan Mocap](https://caizhongang.github.io/projects/HuMMan/) toolchain for multi-view single person SMPL estimation
- Reproduce [MvP](https://arxiv.org/pdf/2111.04076.pdf), a deep-learning-based SOTA for multi-view multi-human 3D pose estimation
- Reproduce [MVPose (single frame)](https://arxiv.org/abs/1901.04111) and [MVPose (temporal tracking and filtering)](https://ieeexplore.ieee.org/document/9492024), two optimization-based methods for multi-view multi-human 3D pose estimation
- Support SMPLify, SMPLifyX, SMPLifyD and SMPLifyXD

New Features

- Add peception module based on mmdet, mmpose and mmtrack
- Add [Shape-aware 3D Pose Optimization](https://ait.ethz.ch/projects/2021/multi-human-pose/)
- Add Keypoints3d optimizer and multi-view single-person api
- Add data_converter and data_visualization for shelf, campus and cmu panoptic datasets
- Add multiple selectors to support more point selection strategies for triangulation
- Add Keypoints and Limbs data structure
- Add multi-way matching registry
- Refactor the pictorial block (c/c++) in python