ASAM: Boosting Segment Anything Model with Adversarial Tuning

arXiv:2405.00256v1 Announce Type: new
Abstract: In the evolving landscape of computer vision, foundation models have emerged as pivotal tools, exhibiting exceptional adaptability to a myriad of tasks. Among these, the Segment Anything Model (SAM) by Meta AI has distinguished itself in image segmentation. However, SAM, like its counterparts, encounters limitations in specific niche applications, prompting a quest for enhancement strategies that do not compromise its inherent capabilities. This paper introduces ASAM, a novel methodology that amplifies SAM's performance through adversarial …

adversarial arxiv boosting cs.cv segment segment anything segment anything model type