30 citations · 61 across the 3 of their papers we have counts for
4 papers
Robustness of SAM: Segment Anything Under Corruptions and Beyond
Yu Qiao, Chaoning Zhang, Taegoo Kang +3
Segment anything model (SAM), as the name suggests, is claimed to be capable of cutting out any object and demonstrates impressive zero-shot transfer performance with the guidance…
A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering
Chaoning Zhang, Joseph Cho, Fachrina Dewi Puspitasari +11
The Segment Anything Model (SAM), developed by Meta AI Research, represents a significant breakthrough in computer vision, offering a robust framework for image and video segmentat…
Attack-SAM: Towards Attacking Segment Anything Model With Adversarial Examples
Chenshuang Zhang, Chaoning Zhang, Taegoo Kang +3
Segment Anything Model (SAM) has attracted significant attention recently, due to its impressive performance on various downstream tasks in a zero-short manner. Computer vision (CV…
A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material
Mengchun Zhang, Maryam Qamar, Taegoo Kang +4
Diffusion models have become a new SOTA generative modeling method in various fields, for which there are multiple survey works that provide an overall survey. With the number of a…