🏃♀️ A curated list about human motion capture, analysis and synthesis.
PyTorch implementation of our graph convolutional network (GCN) for human motion generation from music. Also with paired dance-music data for training!
The source code and pre-trained models for Motion Matters: Neural Motion Transfer for Better Camera Physiological Sensing (WACV 2024, Oral).
(CVPR 2023) MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds
Extract and visualize gait data
CoachMe: A generative instruction model based on motion analysis for sports.
[ECCV 2026] Official implementation of "Language-Guided Transformer Tokenizer for Human Motion Generation."
Official implementation of the paper "MoSa: Motion Generation with Scalable Autoregressive Modelling."
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!
A project that create virtual cycling simulator
SOLIDWORKS Simulation Professional — FEA, motion and fatigue analysis integrated with CAD models.
Official implementation of AAAI 2023 Oral Paper "Frame-Level Label Refinement for Skeleton-Based Weakly-Supervised Action Recognition"
Python interface of C3Dserver software for reading and editing C3D motion capture files
The infant video dataset collected from Youtube with body parsing annotations.
Natural Coordinates with python for biomechanics
A research toolkit for extracting quantitative features from human movement data, offering computational methods to analyze movement qualities like smoothness, bilateral symmetry, contraction/expansion patterns, and synchronization. Built for researchers in motor control, biomechanics, and movement disorders.
Usage of direct linear transformation (camera calibration and point reconstruction) for accurate motion analysis in biomechanical applications.
NintAi is a professional-grade bio-mechanical analysis tool that turns your computer into a high-end bike fitting studio. Inspired by industry leaders like MyVeloFit, NintAi uses YOLOv11 for state-of-the-art tracking and Google Gemini 3 (AI) to provide expert-level written reports
Wearable gait event detection device with real-time gait event-dependent feedback. Heel-strike events accuracy was validated with floor-embedded force plates.
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