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Visual question answering (VQA) is the task of answering questions about an image.
Vqa: Visual question answering. In Proceedings of the IEEE international conference on computer vision . 2425–2433
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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Microsoft coco captions: Data collection and evaluation server
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick. 2015 · 2015
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Making the v in vqa matter: Elevating the role of image understanding in visual question answering. In Proceedings of the IEEE conference on computer vision and pattern recognition . 6904–6913
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017 · 2017
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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, et al · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2017 · 2017
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Image captioning and visual question answering based on attributes and external knowledge
Qi Wu, Chunhua Shen, Peng Wang, Anthony Dick, and Anton Van Den Hengel. 2017 · 2017
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Simple multi-dataset detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 7571–7580
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl. 2022 · 2017
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Vqa-e: Explaining, elaborating, and enhancing your answers for visual questions. In Proceedings of the European Conference on Computer Vision (ECCV) . 552–567
Qing Li, Qingyi Tao, Shafiq Joty, Jianfei Cai, and Jiebo Luo. 2018 · 2018
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Multimodal explanations: Justifying decisions and pointing to the evidence. In Proceedings of the IEEE conference on computer vision and pattern recognition . 8779–8788
Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata, Anna Rohrbach, Bernt Schiele, Trevor Darrell, and Marcus Rohrbach. 2018 · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Kvqa: Knowledge-aware visual question answering. In Proceedings of the AAAI conference on artificial intelligence , Vol. 33. 8876–8884
Sanket Shah, Anand Mishra, Naganand Yadati, and Partha Pratim Talukdar. 2019 · 2019
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End-to-end object detection with transformers. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part I 16 . Springer, 213–229
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko. 2020 · 2020
Cited alongside, same era.
Pali: A jointly-scaled multilingual language-image model
Xi Chen, Xiao Wang, Soravit Changpinyo, AJ Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, et al · 2022
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al · 2022
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Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering. In The 36th Conference on Neural Information Processing Systems (NeurIPS)
Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan. 2022 · 2022
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A-OKVQA: A Benchmark for Visual Question Answering Using World Knowledge. In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part VIII . 146–162
Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, Kenneth Marino, and Roozbeh Mottaghi. 2022 · 2022
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. In International Conference on Learning Representations
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning. In The 35th Conference on Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks
Pan Lu, Liang Qiu, Jiaqi Chen, Tony Xia, Yizhou Zhao, Wei Zhang, Zhou Yu, Xiaodan Liang, and Song-Chun Zhu. 2021 · 2021
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Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
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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Knowledge base graph embedding module design for Visual question answering model
Wenfeng Zheng, Lirong Yin, Xiaobing Chen, Zhiyang Ma, Shan Liu, and Bo Yang. 2021 · 2021
Cited alongside, same era.
Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework. In International Conference on Machine Learning . PMLR, 23318–23340
Peng Wang, An Yang, Rui Men, Junyang Lin, Shuai Bai, Zhikang Li, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang. 2022b
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Image as a foreign language: Beit pretraining for all vision and vision-language tasks
Wenhui Wang, Hangbo Bao, Li Dong, Johan Bjorck, Zhiliang Peng, Qiang Liu, Kriti Aggarwal, Owais Khan Mohammed, Saksham Singhal, Subhojit Som, et al · 2022
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Reltr: Relation transformer for scene graph generation
Yuren Cong, Michael Ying Yang, and Bodo Rosenhahn. 2023 · 2023
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023 · 2023
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Visual spatial reasoning
Fangyu Liu, Guy Emerson, and Nigel Collier. 2023 · 2023
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