Official implementation of "MoMask: Generative Masked Modeling of 3D Human Motions (CVPR2024)"
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Updated
Sep 13, 2024 - Python
Official implementation of "MoMask: Generative Masked Modeling of 3D Human Motions (CVPR2024)"
🏃♀️ A curated list about human motion capture, analysis and synthesis.
Official implementations for "Action2Motion: Conditioned Generation of 3D Human Motions (ACM MultiMedia 2020)"
[SIGGRAPH 2022] ARTEMIS, a novel neural modeling and rendering pipeline for generating ARTiculated neural pets with appEarance and Motion synthesIS.
[NeurIPS 2020] Official PyTorch Implementation of "Residual Force Control for Agile Human Behavior Imitation and Extended Motion Synthesis". NeurIPS 2020.
Interactive Character Control with Auto-Regressive Motion Diffusion Models
Motion Puzzle - Official PyTorch implementation
This is a repository for GraspXL, which can generate objective-drive grasping motions for 500k+ objects with different dexterous hands.
PyTorch implementation of our graph convolutional network (GCN) for human motion generation from music. Also with paired dance-music data for training!
[ECCV 2022] SAGA: Stochastic Whole-Body Grasping with Contact
[ECCV 2024] Official PyTorch implement of paper "ParCo: Part-Coordinating Text-to-Motion Synthesis": http://arxiv.org/abs/2403.18512
Official implementation of "Diverse Motion Stylization for Multiple Style Domains via Spatial-Temporal Graph-Based Generative Model"
Implementation of Constructing Human Motion Manifold with Sequential Networks in PyTorch
Official implementation for "MOCHA: Real-Time Motion Characterization via Context Matching" [SIGGRAPH Asia 2023]
Official dataset and code for "ELMO: Enhanced Real-time LiDAR Motion Capture through Upsampling" and "MOVIN: Real-time Motion Capture using a Single LiDAR"
Project contains: 1. A trained neural model based on the mixture of experts concept to synthesise fast boxing actions 2. An interactive controller that visualises the results of user controlled motion synthesised with the neural model in Unity.
Crowd Simulation Using GANimator
Code that reproduces results for the paper "Adversarial learning for modeling human motion" -
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