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The Segment Anything Model (SAM) has exhibited outstanding performance in various image segmentation tasks.
“Segmentation in the wild,”
1931
Earlier work this paper cites.
“Microsoft coco: Common objects in context,”
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick, · 2014
Earlier work this paper cites.
“Categorical reparameterization with gumbel-softmax,”
Eric Jang, Shixiang Gu, and Ben Poole, · 2016
Earlier work this paper cites.
“Neural discrete representation learning,”
Aaron Van Den Oord, Oriol Vinyals, et al., · 2017
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“Parameter-efficient transfer learning for nlp,”
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly, · 2019
Earlier work this paper cites.
“Towards high-resolution salient object detection,”
Yi Zeng, Pingping Zhang, Zhe Lin, Jianming Zhang, and Huchuan Lu, · 2019
Earlier work this paper cites.
“Deep interactive thin object selection,”
Jun Hao Liew, Scott Cohen, Brian Price, Long Mai, and Jiashi Feng, · 2021
Earlier work this paper cites.
“Deep interactive thin object selection,”
Jun Hao Liew, Scott Cohen, Brian Price, Long Mai, and Jiashi Feng, · 2021
Earlier work this paper cites.
“Highly accurate dichotomous image segmentation,”
Xuebin Qin, Hang Dai, Xiaobin Hu, Deng-Ping Fan, Ling Shao, and Luc Van Gool, · 2022
Earlier work this paper cites.
“Dino: Detr with improved denoising anchor boxes for end-to-end object detection,”
Hao Zhang, Feng Li, Shilong Liu, Lei Zhang, Hang Su, Jun Zhu, Lionel M Ni, and Heung-Yeung Shum, · 2022
Cited alongside, same era.
“Inpaint anything: Segment anything meets image inpainting,”
Tao Yu, Runseng Feng, Ruoyu Feng, Jinming Liu, Xin Jin, Wenjun Zeng, and Zhibo Chen, · 2023
Cited alongside, same era.
“How segment anything model (sam) boost medical image segmentation?,”
Yichi Zhang and Rushi Jiao, · 2023
Cited alongside, same era.
“Baseg: Boundary aware semantic segmentation for autonomous driving,”
Xiaoyang Xiao, Yuqian Zhao, Fan Zhang, Biao Luo, Lingli Yu, Baifan Chen, and Chunhua Yang, · 2023
Cited alongside, same era.
“Foodsam: Any food segmentation,”
Xing Lan, Jiayi Lyu, Hanyu Jiang, Kun Dong, Zehai Niu, Yi Zhang, and Jian Xue, · 2023
Later among the works it cites.
“Segment anything in high quality,”
Lei Ke, Mingqiao Ye, Martin Danelljan, Yifan Liu, Yu-Wing Tai, Chi-Keung Tang, and Fisher Yu, · 2023
Later among the works it cites.
Keyan Chen, Chenyang Liu, Hao Chen, Haotian Zhang, Wenyuan Li, Zhengxia Zou, and Zhenwei Shi, · 2023
Later among the works it cites.
“Surgicalsam: Efficient class promptable surgical instrument segmentation,”
Wenxi Yue, Jing Zhang, Kun Hu, Yong Xia, Jiebo Luo, and Zhiyong Wang, · 2023
Later among the works it cites.
“Sam-u: Multi-box prompts triggered uncertainty estimation for reliable sam in medical image,”
Guoyao Deng, Ke Zou, Kai Ren, Meng Wang, Xuedong Yuan, Sancong Ying, and Huazhu Fu, · 2023
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Zhihe Lu, Zeyu Xiao, Jiawang Bai, Zhiwei Xiong, and Xinchao Wang, · 2023
Cited alongside, same era.
“Matte anything: Interactive natural image matting with segment anything models,”
Jingfeng Yao, Xinggang Wang, Lang Ye, and Wenyu Liu, · 2023
Cited alongside, same era.
“Let segment anything help image dehaze,”
Zheyan Jin, Shiqi Chen, Yueting Chen, Zhihai Xu, and Huajun Feng, · 2023
Cited alongside, same era.
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al., · 2023
Cited alongside, same era.
“Personalize segment anything model with one shot,”
Renrui Zhang, Zhengkai Jiang, Ziyu Guo, Shilin Yan, Junting Pan, Hao Dong, Peng Gao, and Hongsheng Li, · 2023
Cited alongside, same era.
Later among the works it cites.
“Samaug: Point prompt augmentation for segment anything model,”
Haixing Dai, Chong Ma, Zhengliang Liu, Yiwei Li, Peng Shu, Xiaozheng Wei, Lin Zhao, Zihao Wu, Dajiang Zhu, Wei Liu, et al., · 2023
Later among the works it cites.
“Parameter-efficient orthogonal finetuning via butterfly factorization,”
Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, et al., · 2023
Later among the works it cites.
“Grounding dino: Marrying dino with grounded pre-training for open-set object detection,”
Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, et al., · 2023
Later among the works it cites.
“Aim: Adapting image models for efficient video action recognition,”
Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, and Mu Li, · 2023
Later among the works it cites.