4 citations · 5 across the 3 of their papers we have counts for
4 papers · 1 filter
SAMed-2: Selective Memory Enhanced Medical Segment Anything Model
Zhiling Yan, Sifan Song, Dingjie Song +11
Recent "segment anything" efforts show promise by learning from large-scale data, but adapting such models directly to medical images remains challenging due to the complexity of m…
IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain
Hong Huang, Weixiang Sun, Zhijian Wu +4
Recently, the rapid advancements of vision-language models, such as CLIP, leads to significant progress in zero-/few-shot anomaly detection (ZFSAD) tasks. However, most existing CL…
AdvLogo: Adversarial Patch Attack against Object Detectors based on Diffusion Models
Boming Miao, Chunxiao Li, Yao Zhu +4
With the rapid development of deep learning, object detectors have demonstrated impressive performance; however, vulnerabilities still exist in certain scenarios. Current research…
Biomedical SAM 2: Segment Anything in Biomedical Images and Videos
Zhiling Yan, Weixiang Sun, Rong Zhou +8
Medical image segmentation and video object segmentation are essential for diagnosing and analyzing diseases by identifying and measuring biological structures. Recent advances in…