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arXiv Computer Vision By Wenhua Jin, Tiancheng Chen, Sheng Tang, Jiahao Li, Yupeng Liu, Weiqi Zhang, Juntong Fang, Zesong Li

Moving Regions, Not Moving Objects: Segmenting What Actually Moves under Camera Motion

Read the original on arXiv Computer Vision →

The paper introduces MoRSe, a method that segments only the regions that actually move between two frames, rather than labeling entire objects as moving. Unlike prior approaches that rely on instance-level proposals and often misattribute motion to whole objects, MoRSe jointly interprets two frames with a single RGB encoder, eliminating the need for optical flow or separate mask generators. The authors also release MoRSe-5K, a benchmark of 42 sequences designed to test the model’s ability to differentiate moving and stationary regions under various camera and scene motion conditions, and demonstrate that MoRSe outperforms existing moving object segmentation and dense 4D reconstruction methods with fewer false positives.

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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