Camo-M3FD is a curated visible-thermal benchmark dataset for cross-spectral camouflaged pedestrian detection, with annotations and baseline evaluations showing the value of fusion.
Assisted refinement network based on channel information interaction for camouflaged and salient object detection
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
SWNet combines visible and NIR spectra with a Pyramid Vision Transformer, bimodal gated fusion, and edge refinement to outperform prior methods on camouflaged weed detection in the Weeds-Banana dataset.
citing papers explorer
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Camo-M3FD: A New Benchmark Dataset for Cross-Spectral Camouflaged Pedestrian Detection
Camo-M3FD is a curated visible-thermal benchmark dataset for cross-spectral camouflaged pedestrian detection, with annotations and baseline evaluations showing the value of fusion.
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SWNet: A Cross-Spectral Network for Camouflaged Weed Detection
SWNet combines visible and NIR spectra with a Pyramid Vision Transformer, bimodal gated fusion, and edge refinement to outperform prior methods on camouflaged weed detection in the Weeds-Banana dataset.