LAD-COD: Language-Aligned Dense Perception for Camouflaged Object Detection
Camouflaged object detection (COD) aims to segment objects that exhibit high visual similarity to their surroundings, which reduces foreground-background discriminability and weakens boundary evidence across appearance, texture, and structure. Such limitations motivate the use of instruction-conditioned semantics as top-down guidance for identifying which weak visual cues are relevant to the target. Recent segmentation systems built on large multimodal models (LMMs) demonstrate this possibility through instruction-conditioned target embeddings that guide mask decoding. However, in this language-to-mask paradigm, the generated target embedding conditions mainly the mask decoder, leaving th...
| Authors | Shangye Song, Tianzhi Zhu, Syed Ariff Syed Hesham et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 August 2026 |
| Last updated at source | 8 August 2026 |
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