4 papers
Boosting Segment Anything Model to Generalize Visually Non-Salient Scenarios
Guangqian Guo, Pengfei Chen, Yong Guo +3
Segment Anything Model (SAM), known for its remarkable zero-shot segmentation capabilities, has garnered significant attention in the community. Nevertheless, its performance is ch…
Why mamba is effective? Exploit Linear Transformer-Mamba Network for Multi-Modality Image Fusion
Chenguang Zhu, Shan Gao, Huafeng Chen +5
Multi-modality image fusion aims to integrate the merits of images from different sources and render high-quality fusion images. However, existing feature extraction and fusion met…
Just a Hint: Point-Supervised Camouflaged Object Detection
Huafeng Chen, Dian Shao, Guangqian Guo +1
Camouflaged Object Detection (COD) demands models to expeditiously and accurately distinguish objects which conceal themselves seamlessly in the environment. Owing to the subtle di…
SAM-COD: SAM-guided Unified Framework for Weakly-Supervised Camouflaged Object Detection
Huafeng Chen, Pengxu Wei, Guangqian Guo +1
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…