AI RESEARCH
IP-SAM: Prompt-Space Conditioning for Prompt-Absent Camouflaged Object Detection
arXiv CS.CV
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ArXi:2603.27250v1 Announce Type: new Prompt-conditioned foundation segmenters have emerged as a dominant paradigm for image segmentation, where explicit spatial prompts (e.g., points, boxes, masks) guide mask decoding. However, many real-world deployments require fully automatic segmentation, creating a structural mismatch: the decoder expects prompts that are unavailable at inference. Existing adaptations typically modify intermediate features, inadvertently bypassing the model's native prompt interface and weakening prompt-conditioned decoding.