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Numerous recent works have proposed pretraining generic visio-linguistic representations and then finetuning them for downstream vision and language tasks.
LeCun, Y., Boser, B.E., Denker, J.S., Henderson, D., Howard, R.E., Hubbard, W.E., Jackel, L.D.: Handwritten digit recognition with a back-propagation network. In: Advances in neural information processing systems. pp. 396–404 (1990)
1990
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Bigham, J.P., Jayant, C., Ji, H., Little, G., Miller, A., Miller, R.C., Miller, R., Tatarowicz, A., White, B., White, S., et al.: Vizwiz: nearly real-time answers to visual questions. In: Proceedings of the 23nd annual ACM symposium on User interface software and technology. pp. 333–342 (2010)
2010
Earlier work this paper cites.
Yao, B.Z., Yang, X., Lin, L., Lee, M.W., Zhu, S.C.: I2t: Image parsing to text description. Proceedings of the IEEE 98
2010
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Ordonez, V., Kulkarni, G., Berg, T.L.: Im2text: Describing images using 1 million captioned photographs. In: Advances in neural information processing systems. pp. 1143–1151 (2011)
2011
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2014
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Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: European conference on computer vision. pp. 740–755. Springer (2014)
2014
Earlier work this paper cites.
Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C.L., Parikh, D.: VQA: Visual question answering. In: ICCV (2015)
2015
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2015
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2015
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2015
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Doersch, C., Gupta, A., Efros, A.A.: Unsupervised visual representation learning by context prediction. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 1422–1430 (2015)
2015
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Plummer, B.A., Wang, L., Cervantes, C.M., Caicedo, J.C., Hockenmaier, J., Lazebnik, S.: Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models. In: Proceedings of the IEEE international conference on computer vision. pp. 2641–2649 (2015)
2015
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Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: Towards real-time object detection with region proposal networks. In: Advances in neural information processing systems. pp. 91–99 (2015)
2015
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2016
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Lu, J., Yang, J., Batra, D., Parikh, D.: Hierarchical question-image co-attention for visual question answering. In: Advances in neural information processing systems. pp. 289–297 (2016)
2016
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Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., Efros, A.A.: Context encoders: Feature learning by inpainting. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2536–2544 (2016)
2016
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Zhang, R., Isola, P., Efros, A.A.: Colorful image colorization. In: European conference on computer vision. pp. 649–666. Springer (2016)
2016
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2017
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Goyal, Y., Khot, T., Summers-Stay, D., Batra, D., Parikh, D.: 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. pp. 6904–6913 (2017)
2017
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Hu, R., Rohrbach, M., Andreas, J., Darrell, T., Saenko, K.: Modeling relationships in referential expressions with compositional modular networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 1115–1124 (2017)
2017
Earlier work this paper cites.
Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.J., Shamma, D.A., et al.: Visual genome: Connecting language and vision using crowdsourced dense image annotations. International Journal of Computer Vision 123
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Pathak, D., Girshick, R., Dollár, P., Darrell, T., Hariharan, B.: Learning features by watching objects move. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 2701–2710 (2017)
2017
Cited alongside, same era.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. In: Advances in neural information processing systems. pp. 5998–6008 (2017)
2017
Cited alongside, same era.
Biten, A.F., Tito, R., Mafla, A., Gomez, L., Rusinol, M., Valveny, E., Jawahar, C., Karatzas, D.: Scene text visual question answering. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 4291–4301 (2019)
2019
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2019
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2019
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2019
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Xie, S., Girshick, R., Dollar, P., Tu, Z., He, K.: Aggregated residual transformations for deep neural networks. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (July 2017)
2017
Cited alongside, same era.
Anderson, P., He, X., Buehler, C., Teney, D., Johnson, M., Gould, S., Zhang, L.: Bottom-up and top-down attention for image captioning and visual question answering. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 6077–6086 (2018)
2018
Cited alongside, same era.
Caron, M., Bojanowski, P., Joulin, A., Douze, M.: Deep clustering for unsupervised learning of visual features. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 132–149 (2018)
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Gurari, D., Li, Q., Stangl, A.J., Guo, A., Lin, C., Grauman, K., Luo, J., Bigham, J.P.: Vizwiz grand challenge: Answering visual questions from blind people. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 3608–3617 (2018)
2018
Cited alongside, same era.
Lee, K.H., Chen, X., Hua, G., Hu, H., He, X.: Stacked cross attention for image-text matching. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 201–216 (2018)
2018
Cited alongside, same era.
Lu, J., Yang, J., Batra, D., Parikh, D.: Neural baby talk. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 7219–7228 (2018)
2018
Cited alongside, same era.
2019
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2019
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2019
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2019
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2019
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Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I.: Language models are unsupervised multitask learners. OpenAI Blog 1
2019
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Shah, S., Mishra, A., Yadati, N., Talukdar, P.P.: Kvqa: Knowledge-aware visual question answering. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 33, pp. 8876–8884 (2019)
2019
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Singh, A., Natarajan, V., Shah, M., Jiang, Y., Chen, X., Batra, D., Parikh, D., Rohrbach, M.: Towards vqa models that can read. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 8317–8326 (2019)
2019
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2019
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2019
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Wang*, Alex, Pruksachatkun*, Yada, Nangia*, Nikita, Singh*, Amanpreet, Michael, J., Hill, F., Levy, O., Bowman, S.: Superglue: A stickier benchmark for general-purpose language understanding systems. In: Advances in Neural Information Processing Systems. pp. 3261–3275 (2019)
2019
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2019
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Yu, Z., Yu, J., Cui, Y., Tao, D., Tian, Q.: Deep modular co-attention networks for visual question answering. In: CVPR (2019)
2019
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2019
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VQA2 challenge 2019. https://evalai.cloudcv.org/web/challenges/challenge-page/163/leaderboard/498 , accessed: 2020-02-28
2020
Closest in time.