Implicit Motion Handling for Video Camouflaged Object Detection (with Xuelian Cheng, Huan Xiong, Deng-Ping Fan, Yiran Zhong, Mehrtash Harandi and Zongyuan Ge)

This paper shows how to detect camouflaged objects in video by exploiting motion as an implicit cue. When an object is visually indistinguishable from its background in any single frame, its motion relative to the background often reveals it. Rather than using explicit optical flow as an input, the method implicitly encodes motion information through a short-term and long-term feature interaction module, producing the first dedicated video camouflaged object detection system and a new large-scale benchmark (MoCA-Mask).

[CVPR 2022 paper]