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In this paper, we address the challenge of image resolution variation for the Segment Anything Model (SAM).
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Medical sam adapter: Adapting segment anything model for medical image segmentation
Junde Wu, Rao Fu, Huihui Fang, Yuanpei Liu, Zhaowei Wang, Yanwu Xu, Yueming Jin, and Tal Arbel · 2023
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Faster segment anything: Towards lightweight sam for mobile applications
Chaoning Zhang, Dongshen Han, Yu Qiao, Jung Uk Kim, Sung-Ho Bae, Seungkyu Lee, and Choong Seon Hong · 2023
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Customized segment anything model for medical image segmentation
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Salient object detection via integrity learning
Mingchen Zhuge, Deng-Ping Fan, Nian Liu, Dingwen Zhang, Dong Xu, and Ling Shao · 2023
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Omg-seg: Is one model good enough for all segmentation?
Xiangtai Li, Haobo Yuan, Wei Li, Henghui Ding, Size Wu, Wenwei Zhang, Yining Li, Kai Chen, and Chen Change Loy · 2024
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Towards open vocabulary learning: A survey
Jianzong Wu, Xiangtai Li, Shilin Xu, Haobo Yuan, Henghui Ding, Yibo Yang, Xia Li, Jiangning Zhang, Yunhai Tong, Xudong Jiang, Bernard Ghanem, and Dacheng Tao · 2024
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Open-vocabulary sam: Segment and recognize twenty-thousand classes interactively
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Test-time domain generalization for face anti-spoofing
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