Segment Any Motion with Radar: Robust Multimodal Moving-Object Segmentation and Tracking
Moving-object perception must decide which image regions correspond to real motion and keep every instance identified over time. Methods that read motion from appearance, optical flow, or estimated trajectories lose that evidence under poor illumination, adverse weather, reflections, and occlusion. Radar is a natural remedy because it measures radial velocity directly instead of inferring it from photometric correspondence. However, existing benchmarks do not jointly provide radar measurements, dense moving-instance masks, and temporally consistent identities for surveillance. We therefore introduce RGBTR-Motion, a synchronized and calibrated fixed-camera benchmark that pairs RGB, thermal...
| Authors | Jue Wang, Xuan Wang, Hao Zhou et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 September 2026 |
| Last updated at source | 8 September 2026 |
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