Improving 3D Foot Motion Reconstruction in Markerless Monocular Human Motion Capture
State-of-the-art methods can recover accurate overall 3D human body motion from in-the-wild videos. However, they often fail to capture fine-grained articulations, especially in the feet, which are critical for applications such as gait analysis and animation. This limitation results from training datasets with inaccurate foot annotations and limited foot motion diversity. We address this gap with FootMR, a Foot Motion Refinement method that refines foot motion estimated by an existing human recovery model through lifting 2D foot keypoint sequences to 3D. By avoiding direct image input, FootMR circumvents inaccurate image-3D annotation pairs and can instead leverage large-scale motion cap...
| Authors | Tom Wehrbein, Bodo Rosenhahn |
|---|---|
| Primary category | cs.CV |
| Published | 10 March 2026 |
| Last updated at source | 10 March 2026 |
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