PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Control

• URL: http://arxiv.org/abs/2509.24591v2
• Date: Thu, 30 Oct 2025 15:48:32 GMT
• Title: PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Control
• Authors: Haozhuo Zhang, Michele Caprio, Jing Shao, Qiang Zhang, Jian Tang, Shanghang Zhang, Wei Pan,
• Abstract summary: We present PoseDiff, a conditional diffusion model that unifies robot state estimation and control within a single framework.<n>At its core, PoseDiff maps raw visual observations into structured robot states-such as 3D keypoints or joint angles-from a single RGB image.<n>Building upon this foundation, PoseDiff extends naturally to video-to-action inverse dynamics.
• Score: 67.17998939712326
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present PoseDiff, a conditional diffusion model that unifies robot state estimation and control within a single framework. At its core, PoseDiff maps raw visual observations into structured robot states-such as 3D keypoints or joint angles-from a single RGB image, eliminating the need for multi-stage pipelines or auxiliary modalities. Building upon this foundation, PoseDiff extends naturally to video-to-action inverse dynamics: by conditioning on sparse video keyframes generated by world models, it produces smooth and continuous long-horizon action sequences through an overlap-averaging strategy. This unified design enables scalable and efficient integration of perception and control. On the DREAM dataset, PoseDiff achieves state-of-the-art accuracy and real-time performance for pose estimation. On Libero-Object manipulation tasks, it substantially improves success rates over existing inverse dynamics modules, even under strict offline settings. Together, these results show that PoseDiff provides a scalable, accurate, and efficient bridge between perception, planning, and control in embodied AI. The video visualization results can be found on the project page: https://haozhuo-zhang.github.io/PoseDiff-project-page/.

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