Highlights
- Refactor evaluation for MvP, mvpose_tracking, mvpose and fourdag, sharing the same super-class.
- Add smpl visualization and unit test, based on
minimal_pytorch_rasterizer
. Multi-person and multi-gender are supported. - Add mmdeploy for faster human perception.
New Features
- Add
PriorConstraint
optimizer for 3D keypoints, filtering out poorly quality bboxes and limbs. - Add mask in smpl_data. The person whose mask is zero will not be plotted.
- Add function
auto_load_smpl_data
, it chooses a correct class when you forget of which type the npz file is. - Add class Timer for recording average time consumption.
Refactors
- Refactor evaluation metrics including MPJPE, PA-MPJPE, PCK, PCP, mAP, and recall.
Highlights
- Add mview_mperson_end2end_estimator for learning-based method.
- Add SMPLX support and allow smpl_data initiation in mview_sperson_smpl_estimator.
- Add multiple optimizers, detailed joint weights and priors, grad clipping for better SMPLify results.
- Add mediapipe_estimator 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 likemmpose_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.
Highlights
- Add 4D Association Graph, 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, 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
Highlights
- Support HuMMan Mocap toolchain for multi-view single person SMPL estimation
- Reproduce MvP, a deep-learning-based SOTA for multi-view multi-human 3D pose estimation
- Reproduce MVPose (single frame) and MVPose (temporal tracking and filtering), 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
- 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