COD10K-C benchmark shows performance drops in camouflaged object detection under corruptions, with RobustCODLite retaining 92.3% of clean Dice score versus 84-88% for SINet-v2, ZoomNet, and PFNet.
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CLIP-Guided SAM injects CLIP-derived features into SAM via lightweight adapters for semantic conditioning, supporting text and spatial prompts while remaining parameter-efficient and achieving competitive performance.
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COD10K-C: Benchmarking Robustness of Camouflaged Object Detection Under Natural Image Corruptions
COD10K-C benchmark shows performance drops in camouflaged object detection under corruptions, with RobustCODLite retaining 92.3% of clean Dice score versus 84-88% for SINet-v2, ZoomNet, and PFNet.
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CLIP-Guided SAM: Parameter-Efficient Semantic Conditioning for Promptable Segmentation
CLIP-Guided SAM injects CLIP-derived features into SAM via lightweight adapters for semantic conditioning, supporting text and spatial prompts while remaining parameter-efficient and achieving competitive performance.