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The Segment Anything Model (SAM) has demonstrated exceptional performance and versatility, making it a promising tool for various related tasks.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Fully convolutional multi-class multiple instance learning
Deepak Pathak, Evan Shelhamer, Jonathan Long, and Trevor Darrell · 2014
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Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Jifeng Dai, Kaiming He, and Jian Sun · 2015
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What’s the point: Semantic segmentation with point supervision
Amy Bearman, Olga Russakovsky, Vittorio Ferrari, and Li Fei-Fei · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Scribblesup: Scribble-supervised convolutional networks for semantic segmentation
Di Lin, Jifeng Dai, Jiaya Jia, Kaiming He, and Jian Sun · 2016
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
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Simple does it: Weakly supervised instance and semantic segmentation
Anna Khoreva, Rodrigo Benenson, Jan Hosang, Matthias Hein, and Bernt Schiele · 2017
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Learning random-walk label propagation for weakly-supervised semantic segmentation
Paul Vernaza and Manmohan Chandraker · 2017
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Object region mining with adversarial erasing: A simple classification to semantic segmentation approach
Yunchao Wei, Jiashi Feng, Xiaodan Liang, Ming-Ming Cheng, Yao Zhao, and Shuicheng Yan · 2017
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Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation
Jiwoon Ahn and Suha Kwak · 2018
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On regularized losses for weakly-supervised cnn segmentation
Meng Tang, Federico Perazzi, Abdelaziz Djelouah, Ismail Ben Ayed, Christopher Schroers, and Yuri Boykov · 2018
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Weakly-supervised semantic segmentation by iteratively mining common object features
Xiang Wang, Shaodi You, Xi Li, and Huimin Ma · 2018
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Weakly supervised learning of instance segmentation with inter-pixel relations
Jiwoon Ahn, Sunghyun Cho, and Suha Kwak · 2019
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Integral object mining via online attention accumulation
Peng-Tao Jiang, Qibin Hou, Yang Cao, Ming-Ming Cheng, Yunchao Wei, and Hong-Kai Xiong · 2019
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Box-driven class-wise region masking and filling rate guided loss for weakly supervised semantic segmentation
Chunfeng Song, Yan Huang, Wanli Ouyang, and Liang Wang · 2019
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Employing multi-estimations for weakly-supervised semantic segmentation
Junsong Fan, Zhaoxiang Zhang, and Tieniu Tan · 2020
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3d guided weakly supervised semantic segmentation
Weixuan Sun, Jing Zhang, and Nick Barnes · 2020
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Self-supervised equivariant attention mechanism for weakly supervised semantic segmentation
Yude Wang, Jie Zhang, Meina Kan, Shiguang Shan, and Xilin Chen · 2020
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Causal intervention for weakly-supervised semantic segmentation
Dong Zhang, Hanwang Zhang, Jinhui Tang, Xiansheng Hua, and Qianru Sun · 2020
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Splitting vs. merging: Mining object regions with discrepancy and intersection loss for weakly supervised semantic segmentation
Tianyi Zhang, Guosheng Lin, Weide Liu, Jianfei Cai, and Alex Kot · 2020
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Discriminative region suppression for weakly-supervised semantic segmentation
Beomyoung Kim, Sangeun Han, and Junmo Kim · 2021
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Unlocking the potential of ordinary classifier: Class-specific adversarial erasing framework for weakly supervised semantic segmentation
Hyeokjun Kweon, Sung-Hoon Yoon, Hyeonseong Kim, Daehee Park, and Kuk-Jin Yoon · 2021
Complementary patch for weakly supervised semantic segmentation
Fei Zhang, Chaochen Gu, Chenyue Zhang, and Yuchao Dai · 2021
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Self-supervised image-specific prototype exploration for weakly supervised semantic segmentation
Qi Chen, Lingxiao Yang, Jian-Huang Lai, and Xiaohua Xie · 2022
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Class re-activation maps for weakly-supervised semantic segmentation
Zhaozheng Chen, Tan Wang, Xiongwei Wu, Xian-Sheng Hua, Hanwang Zhang, and Qianru Sun · 2022
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Weakly supervised semantic segmentation by pixel-to-prototype contrast
Ye Du, Zehua Fu, Qingjie Liu, and Yunhong Wang · 2022
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L2g: A simple local-to-global knowledge transfer framework for weakly supervised semantic segmentation
Peng-Tao Jiang, Yuqi Yang, Qibin Hou, and Yunchao Wei · 2022
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Reducing information bottleneck for weakly supervised semantic segmentation
Jungbeom Lee, Jooyoung Choi, Jisoo Mok, and Sungroh Yoon · 2021
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Anti-adversarially manipulated attributions for weakly and semi-supervised semantic segmentation
Jungbeom Lee, Eunji Kim, and Sungroh Yoon · 2021
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Bbam: Bounding box attribution map for weakly supervised semantic and instance segmentation, 2021
Jungbeom Lee, Jihun Yi, Chaehun Shin, and Sungroh Yoon · 2021
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Railroad is not a train: Saliency as pseudo-pixel supervision for weakly supervised semantic segmentation
Seungho Lee, Minhyun Lee, Jongwuk Lee, and Hyunjung Shim · 2021
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Yi Li, Yiqun Duan, Zhanghui Kuang, Yimin Chen, Wayne Zhang, and Xiaomeng Li · 2021
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Pseudo-mask matters in weakly-supervised semantic segmentation
Yi Li, Zhanghui Kuang, Liyang Liu, Yimin Chen, and Wayne Zhang · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
Jungbeom Lee, Seong Joon Oh, Sangdoo Yun, Junsuk Choe, Eunji Kim, and Sungroh Yoon · 2022
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Expansion and shrinkage of localization for weakly-supervised semantic segmentation
Jinlong Li, Zequn Jie, Xu Wang, Xiaolin Wei, and Lin Ma · 2022
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
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Weakly-supervised semantic segmentation with visual words learning and hybrid pooling
Lixiang Ru, Bo Du, Yibing Zhan, and Chen Wu · 2022
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Learning affinity from attention: End-to-end weakly-supervised semantic segmentation with transformers
Lixiang Ru, Yibing Zhan, Baosheng Yu, and Bo Du · 2022
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Inferring the class conditional response map for weakly supervised semantic segmentation
Weixuan Sun, Jing Zhang, and Nick Barnes · 2022
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C2am: Contrastive learning of class-agnostic activation map for weakly supervised object localization and semantic segmentation
Jinheng Xie, Jianfeng Xiang, Junliang Chen, Xianxu Hou, Xiaodong Zhao, and Linlin Shen · 2022
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Multi-class token transformer for weakly supervised semantic segmentation
Lian Xu, Wanli Ouyang, Mohammed Bennamoun, Farid Boussaid, and Dan Xu · 2022
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Out-of-candidate rectification for weakly supervised semantic segmentation, 2023
Zesen Cheng, Pengchong Qiao, Kehan Li, Siheng Li, Pengxu Wei, Xiangyang Ji, Li Yuan, Chang Liu, and Jie Chen · 2023
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Segment anything, 2023
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick · 2023
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Clip is also an efficient segmenter: A text-driven approach for weakly supervised semantic segmentation, 2023
Yuqi Lin, Minghao Chen, Wenxiao Wang, Boxi Wu, Ke Li, Binbin Lin, Haifeng Liu, and Xiaofei He · 2023
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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, and Lei Zhang · 2023
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