A curated, public list of resources for biomechanics and human motion analysis: datasets, processing tools, software for simulation, educational videos, lectures, etc.
[RSS 2024]: Expressive Whole-Body Control for Humanoid Robots
A curated list about human motion capture, analysis and synthesis.
Official PyTorch implementation of the paper "TEMOS: Generating diverse human motions from textual descriptions", ECCV 2022 (Oral)
GRAB: A Dataset of Whole-Body Human Grasping of Objects
An aggregation of human motion understanding research.
[CVPR 2024] Official Implementation of "Seamless Human Motion Composition with Blended Positional Encodings".
[NeurIPS 2023] InsActor: Instruction-driven Physics-based Characters
Official implementation of TRACE, the TRAjectory Diffusion Model for Controllable PEdestrians, from the CVPR 2023 paper: "Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion".
Forecasting Characteristic 3D Poses of Human Actions (CVPR'22)
PyTorch implementation of our graph convolutional network (GCN) for human motion generation from music. Also with paired dance-music data for training!
Official implementation of TeSMo, a method for text-controlled scene-aware motion generation, from the ECCV 2024 paper: "Generating Human Interaction Motions in Scenes with Text Control".
Text-driven human motion generation surveys, datasets and models.
[ECCV 2022] SAGA: Stochastic Whole-Body Grasping with Contact
[CVPRW 2024] Official Implementation of "in2IN: Leveraging individual Information to Generate Human INteractions".
[CVPR 2023] NeuralPCI: Spatio-temporal Neural Field for 3D Point Cloud Multi-frame Non-linear Interpolation
Implementation of Constructing Human Motion Manifold with Sequential Networks in PyTorch
Official code of [AAAI2024] Expressive Forecasting of 3D Whole-body Human Motions
Code for the ECCV'22 paper "Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos".
Code and dataset of human retargeting approach to transfer motion and appearance between monocular videos. Check the examples from our dataset with several paired actors and motions!
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