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Referring expression segmentation (RES), a task that involves localizing specific instance-level objects based on free-form linguistic descriptions, has emerged as a crucial frontier in human-AI interaction.
A simple semi-supervised learning framework for object detection
Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li, Han Zhang, Chen-Yu Lee, and Tomas Pfister · 2005
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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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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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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
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Segmentation from natural language expressions
Ronghang Hu, Marcus Rohrbach, and Trevor Darrell · 2016
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Modeling context between objects for referring expression understanding
Varun K Nagaraja, Vlad I Morariu, and Larry S Davis · 2016
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Modeling context in referring expressions , pages 69–85
Licheng Yu, Patrick Poirson, Shan Yang, Alexander C Berg, and Tamara L Berg · 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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Recurrent multimodal interaction for referring image segmentation
Chenxi Liu, Zhe Lin, Xiaohui Shen, Jimei Yang, Xin Lu, and Alan Yuille · 2017
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Semi supervised semantic segmentation using generative adversarial network
Nasim Souly, Concetto Spampinato, and Mubarak Shah · 2017
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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Referring image segmentation via recurrent refinement networks
Ruiyu Li, Kaican Li, Yi-Chun Kuo, Michelle Shu, Xiaojuan Qi, Xiaoyong Shen, and Jiaya Jia · 2018
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See-through-text grouping for referring image segmentation
Ding-Jie Chen, Songhao Jia, Yi-Chen Lo, Hwann-Tzong Chen, and Tyng-Luh Liu · 2019
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Semi-supervised semantic segmentation needs strong, high-dimensional perturbations
Geoff French, Timo Aila, Samuli Laine, Michal Mackiewicz, and Graham Finlayson · 2019
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Semi-supervised semantic segmentation with high-and low-level consistency
Sudhanshu Mittal, Maxim Tatarchenko, and Thomas Brox · 2019
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Reinforced cross-modal matching and self-supervised imitation learning for vision-language navigation
Xin Wang, Qiuyuan Huang, Asli Celikyilmaz, Jianfeng Gao, Dinghan Shen, Yuan-Fang Wang, William Yang Wang, and Lei Zhang · 2019
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Cross-modal self-attention network for referring image segmentation
Linwei Ye, Mrigank Rochan, Zhi Liu, and Yang Wang · 2019
Cited alongside, same era.
Bi-directional relationship inferring network for referring image segmentation
Zhiwei Hu, Guang Feng, Jiayu Sun, Lihe Zhang, and Huchuan Lu · 2020
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Cascade grouped attention network for referring expression segmentation
Gen Luo, Yiyi Zhou, Rongrong Ji, Xiaoshuai Sun, Jinsong Su, Chia-Wen Lin, and Qi Tian · 2020
Cited alongside, same era.
Semi-supervised semantic segmentation with cross-consistency training
Yassine Ouali, Céline Hudelot, and Myriam Tami · 2020
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Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard Hovy, Thang Luong, and Quoc Le · 2020
Cited alongside, same era.
Pseudoseg: Designing pseudo labels for semantic segmentation
Pixel contrastive-consistent semi-supervised semantic segmentation
Yuanyi Zhong, Bodi Yuan, Hong Wu, Zhiqiang Yuan, Jian Peng, and Yu-Xiong Wang · 2021
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Learning statistical texture for semantic segmentation
Lanyun Zhu, Deyi Ji, Shiping Zhu, Weihao Gan, Wei Wu, and Junjie Yan · 2021
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Unbiased subclass regularization for semi-supervised semantic segmentation
Dayan Guan, Jiaxing Huang, Aoran Xiao, and Shijian Lu · 2022
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Semi-supervised neuron segmentation via reinforced consistency learning
Wei Huang, Chang Chen, Zhiwei Xiong, Yueyi Zhang, Xuejin Chen, Xiaoyan Sun, and Feng Wu · 2022
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Restr: Convolution-free referring image segmentation using transformers
Namyup Kim, Dongwon Kim, Cuiling Lan, Wenjun Zeng, and Suha Kwak · 2022
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Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, and Tomas Pfister · 2020
Cited alongside, same era.
Semi-supervised semantic segmentation with cross pseudo supervision
Xiaokang Chen, Yuhui Yuan, Gang Zeng, and Jingdong Wang · 2021
Cited alongside, same era.
Vision-language transformer and query generation for referring segmentation
Henghui Ding, Chang Liu, Suchen Wang, and Xudong Jiang · 2021
Cited alongside, same era.
Encoder fusion network with co-attention embedding for referring image segmentation
Guang Feng, Zhiwei Hu, Lihe Zhang, and Huchuan Lu · 2021
Cited alongside, same era.
Re-distributing biased pseudo labels for semi-supervised semantic segmentation: A baseline investigation
Ruifei He, Jihan Yang, and Xiaojuan Qi · 2021
Cited alongside, same era.
Atso: Asynchronous teacher-student optimization for semi-supervised image segmentation
Xinyue Huo, Lingxi Xie, Jianzhong He, Zijie Yang, Wengang Zhou, Houqiang Li, and Qi Tian · 2021
Cited alongside, same era.
Locate then segment: A strong pipeline for referring image segmentation
Ya Jing, Tao Kong, Wei Wang, Liang Wang, Lei Li, and Tieniu Tan · 2021
Cited alongside, same era.
Jianzong Wu, Xiangtai Li, Xia Li, Henghui Ding, Yunhai Tong, and Dacheng Tao · 2022
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Conservative-progressive collaborative learning for semi-supervised semantic segmentation
Siqi Fan, Fenghua Zhu, Zunlei Feng, Yisheng Lv, Mingli Song, and Fei-Yue Wang · 2023
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Beyond one-to-one: Rethinking the referring image segmentation
Yutao Hu, Qixiong Wang, Wenqi Shao, Enze Xie, Zhenguo Li, Jungong Han, and Ping Luo · 2023
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Cafs: Class adaptive framework for semi-supervised semantic segmentation
Jingi Ju, Hyeoncheol Noh, Yooseung Wang, Minseok Seo, and Dong-Geol Choi · 2023
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Shatter and gather: Learning referring image segmentation with text supervision
Dongwon Kim, Namyup Kim, Cuiling Lan, and Suha Kwak · 2023
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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
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Weakly supervised referring image segmentation with intra-chunk and inter-chunk consistency
Jungbeom Lee, Sungjin Lee, Jinseok Nam, Seunghak Yu, Jaeyoung Do, and Tara Taghavi · 2023
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Fuzzy positive learning for semi-supervised semantic segmentation
Pengchong Qiao, Zhidan Wei, Yu Wang, Zhennan Wang, Guoli Song, Fan Xu, Xiangyang Ji, Chang Liu, and Jie Chen · 2023
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Corrmatch: Label propagation via correlation matching for semi-supervised semantic segmentation
Boyuan Sun, Yuqi Yang, Le Zhang, Ming-Ming Cheng, and Qibin Hou · 2023
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Contrastive grouping with transformer for referring image segmentation
Jiajin Tang, Ge Zheng, Cheng Shi, and Sibei Yang · 2023
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Improving semi-supervised semantic segmentation with dual-level siamese structure network
Zhibo Tian, Xiaolin Zhang, Peng Zhang, and Kun Zhan · 2023
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Revisiting weak-to-strong consistency in semi-supervised semantic segmentation
Lihe Yang, Lei Qi, Litong Feng, Wayne Zhang, and Yinghuan Shi · 2023
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Zero-shot referring image segmentation with global-local context features
Seonghoon Yu, Paul Hongsuck Seo, and Jeany Son · 2023
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