A framework uses modality-agnostic prompts to adapt SAM for multi-modal camouflaged object detection, with a mask refine module for better boundaries.
Sam2-unet: Segment anything 2 makes strong encoder for natural and medical image segmentation,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Defines SML task for localizing semantic edits and proposes TRACE framework with semantic anchoring, perturbation sensing, and constrained reasoning that outperforms prior IML methods on a custom benchmark.
citing papers explorer
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Modality-Agnostic Prompt Learning for Multi-Modal Camouflaged Object Detection
A framework uses modality-agnostic prompts to adapt SAM for multi-modal camouflaged object detection, with a mask refine module for better boundaries.
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Semantic Manipulation Localization
Defines SML task for localizing semantic edits and proposes TRACE framework with semantic anchoring, perturbation sensing, and constrained reasoning that outperforms prior IML methods on a custom benchmark.