shan gao* — accepted AI-conference papers

2024

Just a Hint: Point-Supervised Camouflaged Object Detection

Huafeng Chen, Dian SHAO*, Guangqian Guo, shan gao*

ECCV 2024poster

"Camouflaged Object Detection (COD) demands models to expeditiously and accurately distinguish objects which conceal themselves seamlessly in the environment. Owing to the subtle differences and ambiguous boundaries, COD is not only a remarkably challenging task for models but also for human annotat…

Cited by 4 Source ↗PDF ↗Scholar ↗

2024

SAM-COD: SAM-guided Unified Framework for Weakly-Supervised Camouflaged Object Detection

Huafeng Chen, Pengxu Wei, Guangqian Guo, Shan Gao*

ECCV 2024poster

"Most Camouflaged Object Detection (COD) methods heavily rely on mask annotations, which are time-consuming and labor-intensive to acquire. Existing weakly-supervised COD approaches exhibit significantly inferior performance compared to fully-supervised methods and struggle to simultaneously support…

Cited by 9 Source ↗PDF ↗Scholar ↗