Mofafa's Stars
facebookresearch/pytorch3d
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
threestudio-project/threestudio
A unified framework for 3D content generation.
DeepLabCut/DeepLabCut
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
NVIDIAGameWorks/kaolin
A PyTorch Library for Accelerating 3D Deep Learning Research
jonbarron/website
autonomousvision/sdfstudio
A Unified Framework for Surface Reconstruction
autonomousvision/unimatch
[TPAMI'23] Unifying Flow, Stereo and Depth Estimation
IDEA-Research/X-Pose
[ECCV 2024] Official implementation of the paper "X-Pose: Detecting Any Keypoints"
facebookresearch/banmo
BANMo Building Animatable 3D Neural Models from Many Casual Videos
akanazawa/cmr
Project repo for Learning Category-Specific Mesh Reconstruction from Image Collections
cbsudux/Human-Pose-Estimation-101
Basics of 2D and 3D Human Pose Estimation.
lab4d-org/lab4d
A framework for 4D reconstruction from monocular videos.
JiahuiLei/GART
GART: Gaussian Articulated Template Models
anl13/animal_papers
Awesome papers for markerless animal motion capture and 3D reconstruction.
google/lasr
Code for "LASR: Learning Articulated Shape Reconstruction from a Monocular Video". CVPR 2021.
HaiminLuo/Artemis
[SIGGRAPH 2022] ARTEMIS, a novel neural modeling and rendering pipeline for generating ARTiculated neural pets with appEarance and Motion synthesIS.
benjiebob/SMALify
This repository contains an implementation for performing 3D animal (quadruped) reconstruction from a monocular image or video. The system adapts the pose (limb positions) and shape (animal type/height/weight) parameters for the SMAL deformable quadruped model, as well as camera parameters until the projected SMAL model aligns with 2D keypoints and silhouette segmentations extracted from the input frame(s).
elliottwu/MagicPony
🎠 MagicPony: Learning Articulated 3D Animals in the Wild (CVPR 2023)
Junyi42/GeoAware-SC
Official Implementation of paper "Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence"
benjiebob/StanfordExtra
12k labelled instances of dogs in-the-wild with 2D keypoint and segmentations. Dataset released with our ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop.
haoz19/MagicPose4D
Code for MagicPose4D: Crafting Articulated Models with Appearance and Motion Control
gengshan-y/viser
ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction. NeurIPS 2021.
benjiebob/WLDO
Code for paper ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop.
benjiebob/BADJA
Benchmark Animal Dataset of Joint Annotations (BADJA) with example code, as introduced in "Creatures Great and SMAL: Recovering the shape and motion of animals from video" (ACCV 2018).
chaneyddtt/ScarceNet
VICO-UoE/SphericalMaps
robot-perception-group/smalify
pytorch-based articulated animal model (SMAL) fitting
tomasjakab/Farm3D
MehmetAygun/saor
SAOR: Single-View Articulated Object Reconstruction, CVPR 2024
chhankyao/artic3d_recon