Search Results for author:
Found 3 papers, 2 papers with code
ASAM: Boosting Segment Anything Model with Adversarial Tuning
In the evolving landscape of computer vision, foundation models have emerged as pivotal tools, exhibiting exceptional adaptability to a myriad of tasks.
Zero-Shot Co-salient Object Detection Framework
Despite recent advancements in deep learning models, these models still rely on training with well-annotated CoSOD datasets.
Can SAM Segment Anything? When SAM Meets Camouflaged Object Detection
In this study, we try to ask if SAM can address the COD task and evaluate the performance of SAM on the COD benchmark by employing maximum segmentation evaluation and camouflage location evaluation.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
