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Multi-label image classification is the task of predicting a set of labels corresponding to objects, attributes or other entities present in an image.
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Yuhong Guo and Suicheng Gu · 2011
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Hongyu Su and Juho Rousu · 2013
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Multi-label image classification with a probabilistic label enhancement model
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Sparse local embeddings for extreme multi-label classification
Kush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, and Prateek Jain · 2015
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Deep learning
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Kazuyuki Hara, Daisuke Saitoh, and Hayaru Shouno · 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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Learning structured inference neural networks with label relations
Hexiang Hu, Guang-Tong Zhou, Zhiwei Deng, Zicheng Liao, and Greg Mori · 2016
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, and Li Fei-Fei · 2016
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Multi-evidence filtering and fusion for multi-label classification, object detection and semantic segmentation based on weakly supervised learning
Weifeng Ge, Sibei Yang, and Yizhou Yu · 2018
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Multi-label zero-shot learning with structured knowledge graphs
Chung-Wei Lee, Wei Fang, Chih-Kuan Yeh, and Yu-Chiang Frank Wang · 2018
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Convnets and imagenet beyond accuracy: Understanding mistakes and uncovering biases
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Feedback-prop: Convolutional neural network inference under partial evidence
Tianlu Wang, Kota Yamaguchi, and Vicente Ordonez · 2018
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Conditional graphical lasso for multi-label image classification
Qiang Li, Maoying Qiao, Wei Bian, and Dacheng Tao · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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Cnn-rnn: A unified framework for multi-label image classification
Jiang Wang, Yi Yang, Junhua Mao, Zhiheng Huang, Chang Huang, and Wei Xu · 2016
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Hcp: A flexible cnn framework for multi-label image classification
Y. Wei, W. Xia, M. Lin, J. Huang, B. Ni, J. Dong, Y. Zhao, and S. Yan · 2016
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Exploit bounding box annotations for multi-label object recognition
Hao Yang, Joey Tianyi Zhou, Yu Zhang, Bin-Bin Gao, Jianxin Wu, and Jianfei Cai · 2016
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End-to-end learning for structured prediction energy networks
David Belanger, Bishan Yang, and Andrew McCallum · 2017
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Partial multi-label learning
Ming-Kun Xie and Sheng-Jun Huang · 2018
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Learning semantic-specific graph representation for multi-label image recognition
Tianshui Chen, Muxin Xu, Xiaolu Hui, Hefeng Wu, and Liang Lin · 2019
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Multi-Label Image Recognition with Graph Convolutional Networks
Zhao-Min Chen, Xiu-Shen Wei, Peng Wang, and Yanwen Guo · 2019
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Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov · 2019
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Learning a deep convnet for multi-label classification with partial labels
Thibaut Durand, Nazanin Mehrasa, and Greg Mori · 2019
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Neural message passing for multi-label classification
Jack Lanchantin, Arshdeep Sekhon, and Yanjun Qi · 2019
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Neural message passing for multi-label classification
Jack Lanchantin, Arshdeep Sekhon, and Yanjun Qi · 2019
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Adaptive attention span in transformers
Sainbayar Sukhbaatar, Edouard Grave, Piotr Bojanowski, and Armand Joulin · 2019
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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Knowledge-guided multi-label few-shot learning for general image recognition
Tianshui Chen, Liang Lin, Xiaolu Hui, Riquan Chen, and Hefeng Wu · 2020
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Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, and Percy Liang · 2020
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Plugin networks for inference under partial evidence
Michal Koperski, Tomasz Konopczynski, Rafal Nowak, Piotr Semberecki, and Tomasz Trzcinski · 2020
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Exploiting weakly supervised visual patterns to learn from partial annotations
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