SOURCE-LINKED INTELLIGENCE
DynEoMT: Learning Object Dynamicity from Online Segmentation Queries
Video segmentation models recognize and track objects over time, but they do not indicate whether each segmented region moves independently of the observing camera. This dynamicity attribute cannot be inferred from semantics alone and is confounded by camera ego-motion. We introduce \method, an online framework that augments query-based video segmentation with region-level dynamicity prediction. It jointly produces the original segmentation outputs and a dynamic or static state for each predicted region. At inference, DynEoMT uses only the current frame and propagated queries, without optical
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- arXiv · AI, language, vision and robotics · 2026-09-13T12:16:47.000Z
First collected: 2026-09-20T12:21:05.240Z. This is not the publication date.