FlowHMR: Physically Plausible Motion Capture from Video
cs.CV
Submitted: 2026-10-02
Updated: 2026-10-02
Comments: Project page: https://flowhmr.github.io/ Code: https://github.com/flowhmr/flowhmr
Code: https://github.com/flowhmr/flowhmr
Project page: https://flowhmr.github.io
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Visual Imitation Enables Contextual Humanoid Control
- Retargeting Matters: General Motion Retargeting for Humanoid Motion Tracking
- Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
- YOLOX: Exceeding YOLO Series in 2021
- D&D: Learning Human Dynamics from Dynamic Camera
- MixGRPO: Unlocking Flow-based GRPO Efficiency with Mixed ODE-SDE
- Back to Basics: Let Denoising Generative Models Denoise
- GenTrack: Physical Alignment for Robot-Native Motion Generation and Zero-Shot Humanoid Tracking
- Flow Matching for Generative Modeling
- Flow-GRPO: Training Flow Matching Models via Online RL
- Perpetual Humanoid Control for Real-time Simulated Avatars
- Universal Humanoid Motion Representations for Physics-Based Control
- Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning
- Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning
- Kimodo: Scaling Controllable Human Motion Generation
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- HY-Motion 1.0: Scaling Flow Matching Models for Text-To-Motion Generation
- 3D Human Pose Estimation via Intuitive Physics
- SimDiff: Simulator-constrained Diffusion Model for Physically Plausible Motion Generation
- DanceGRPO: Unleashing GRPO on Visual Generation
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