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Vision-language models like CLIP excel at recognizing the single, prominent object in a scene.
A mathematical theory of communication
Claude Elwood Shannon · 1948
Earlier work this paper cites.
Possible principles underlying the transformation of sensory messages
Horace B Barlow et al · 1961
Earlier work this paper cites.
On the estimation of entropy
Peter Hall and Sally C Morton · 1993
Earlier work this paper cites.
The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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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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The role of context for object detection and semantic segmentation in the wild
Roozbeh Mottaghi, Xianjie Chen, Xiaobai Liu, Nam-Gyu Cho, Seong-Whan Lee, Sanja Fidler, Raquel Urtasun, and Alan Yuille · 2014
Earlier work this paper cites.
Deep learning and the information bottleneck principle
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End-to-end optimized image compression
Johannes Ballé, Valero Laparra, and Eero P Simoncelli · 2016
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
Earlier work this paper cites.
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Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2017
Earlier work this paper cites.
Coco-stuff: Thing and stuff classes in context
Holger Caesar, Jasper Uijlings, and Vittorio Ferrari · 2018
Earlier work this paper cites.
Estimating differential entropy under gaussian convolutions
Ziv Goldfeld, Kristjan Greenewald, and Yury Polyanskiy · 2018
Earlier work this paper cites.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Zero-shot semantic segmentation
Maxime Bucher, Tuan-Hung Vu, Matthieu Cord, and Patrick Pérez · 2019
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Yongqin Xian, Subhabrata Choudhury, Yang He, Bernt Schiele, and Zeynep Akata · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Randaugment: Practical automated data augmentation with a reduced search space
Ekin D Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V Le · 2020
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Momentum contrast for unsupervised visual representation learning
Exploring structured semantic prior for multi label recognition with incomplete labels
Zixuan Ding, Ao Wang, Hui Chen, Qiang Zhang, Pengzhang Liu, Yongjun Bao, Weipeng Yan, and Jungong Han · 2023
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Maskclip: Masked self-distillation advances contrastive language-image pretraining
Xiaoyi Dong, Jianmin Bao, Yinglin Zheng, Ting Zhang, Dongdong Chen, Hao Yang, Ming Zeng, Weiming Zhang, Lu Yuan, Dong Chen, et al · 2023
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High-dimensional smoothed entropy estimation via dimensionality reduction
Kristjan Greenewald, Brian Kingsbury, and Yuancheng Yu · 2023
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Texts as images in prompt tuning for multi-label image recognition
Zixian Guo, Bowen Dong, Zhilong Ji, Jinfeng Bai, Yiwen Guo, and Wangmeng Zuo · 2023
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Dualcoop++: Fast and effective adaptation to multi-label recognition with limited annotations
Ping Hu, Ximeng Sun, Stan Sclaroff, and Kate Saenko · 2023
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Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Data-efficient image recognition with contrastive predictive coding
Olivier Henaff · 2020
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Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 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
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Asymmetric loss for multi-label classification
Tal Ridnik, Emanuel Ben-Baruch, Nadav Zamir, Asaf Noy, Itamar Friedman, Matan Protter, and Lihi Zelnik-Manor · 2021
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Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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Dualcoop: Fast adaptation to multi-label recognition with limited annotations
Ximeng Sun, Ping Hu, and Kate Saenko · 2022
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Segment anything
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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Clip is also an efficient segmenter: A text-driven approach for weakly supervised semantic segmentation
Yuqi Lin, Minghao Chen, Wenxiao Wang, Boxi Wu, Ke Li, Binbin Lin, Haifeng Liu, and Xiaofei He · 2023
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Mixture-based estimation of entropy
Stéphane Robin and Luca Scrucca · 2023
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Grounding everything: Emerging localization properties in vision-language transformers
Walid Bousselham, Felix Petersen, Vittorio Ferrari, and Hilde Kuehne · 2024
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Improving multi-label recognition using class co-occurrence probabilities
Samyak Rawlekar, Shubhang Bhatnagar, Vishnuvardhan Pogunulu Srinivasulu, and Narendra Ahuja · 2024
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A closer look at the explainability of contrastive language-image pre-training
Yi Li, Hualiang Wang, Yiqun Duan, Jiheng Zhang, and Xiaomeng Li · 2025
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Positivecoop: Rethinking prompting strategies for multi-label recognition with partial annotations
Samyak Rawlekar, Shubhang Bhatnagar, and Narendra Ahuja · 2025
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