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arXiv Computer Vision By Yinqi Chen, E Li, Shuaijun Wang, Weiyuan Peng, Meiying Zhang, Qi Hao

MeshBind: Point-to-Mesh Binding for Non-Rigid Scene Flow Automatic Annotation

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MeshBind introduces an automatic annotation pipeline that generates per-point scene flow for non‑rigid objects such as pedestrians by reconstructing articulated mesh models from six surround cameras and registering them to LiDAR data. The method employs a local‑frame binding technique that attaches each point to a mesh via a per‑triangle tangent‑normal frame, and a three‑layer flow registration pipeline that compensates ego‑vehicle motion, performs box binding, and applies mesh binding to produce full‑scene flow. MeshBind is implemented in the SF‑Studio tool, and the authors release the SUScape‑Flow Benchmark (SFB), a large‑scale dataset with 41k frames of per‑point non‑rigid pedestrian annotations and a comprehensive evaluation protocol, demonstrating that fine‑tuning on SFB reduces endpoint error by 2‑3× and equalizes non‑rigid and rigid EPE.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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