Explicit Motion Handling and Interactive Prompting for Video Camouflaged Object Detection

Understand

Camouflage poses challenges in distinguishing a static target, whereas any movement of the target can break this disguise.

• Existing video camouflaged object detection (VCOD) approaches take noisy motion estimation as input or model motion implicitly, restricting detection performance in complex dynamic scenes.
• In this paper, we propose a novel Explicit Motion handling and Interactive Prompting framework for VCOD, dubbed EMIP, which handles motion cues explicitly using a frozen pre-trained optical flow fundamental model.
• EMIP is characterized by a two-stream architecture for simultaneously conducting camouflaged segmentation and optical flow estimation.