SOURCE-LINKED INTELLIGENCE
LGFN: Lightweight Gated RGB-Polarization Fusion with Modality-Availability Conditioning for Camouflaged Object Detection
Camouflaged object detection (COD) is an important engineering task in intelligent optical perception, but it remains challenging when targets closely resemble their surroundings. Polarization imaging provides complementary physical cues, whereas existing methods typically assume fixed multimodal input configurations and entangle intra-polarization coordination with interaction between red-green-blue (RGB) and polarization representations. We propose LGFN, a lightweight gated RGB-polarization fusion framework supporting separately optimized RGB-only and polarization-assisted configurations. A
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-11T12:57:37.000Z
First collected: 2026-09-20T18:22:04.777Z. This is not the publication date.