TAPVid-MV: A Benchmark for Tracking Any Point in 3D Across Multiple Views
Multi-camera systems are increasingly practical for robotics, AR/VR, and autonomous driving because complementary views reduce depth ambiguity and preserve visibility under occlusion. Existing point-tracking benchmarks, however, focus on a single video or static multi-camera rigs. None test long-term 3D point tracking across several synchronized views under camera motion. We introduce TAPVid-MV (Tracking Any Point in Video across Multiple Views), the first benchmark for this setting. It contains a curated set of 238 sequences, 1,004 calibrated camera streams, and 74,147 point tracks across seven subsets spanning indoor and outdoor domains, from robotics and human activity to driving and s...
| Authors | Skanda Koppula, Frano Rajic, Abdullah Faiz Ur Rahman et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 September 2026 |
| Last updated at source | 9 October 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.