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Convolutional operations have two limitations: (1) do not explicitly model where to focus as the same filter is applied to all the positions, and (2) are unsuitable for modeling long-range dependencies as they only operate on a small neighborhood.
Srinivas, N., Krause, A., Kakade, S.M., Seeger, M.W.: Gaussian process optimization in the bandit setting: No regret and experimental design. In: ICML (2009)
2009
Earlier work this paper cites.
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: NeurIPS (2012)
2012
Earlier work this paper cites.
Snoek, J., Larochelle, H., Adams, R.P.: Practical bayesian optimization of machine learning algorithms. In: NeurIPS (2012)
2012
Earlier work this paper cites.
Simonyan, K., Zisserman, A.: Two-stream convolutional networks for action recognition in videos. In: NeurIPS (2014)
2014
Earlier work this paper cites.
Donahue, J., Anne Hendricks, L., Guadarrama, S., Rohrbach, M., Venugopalan, S., Saenko, K., Darrell, T.: Long-term recurrent convolutional networks for visual recognition and description. In: CVPR (2015)
2015
Earlier work this paper cites.
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: Going deeper with convolutions. In: CVPR (2015)
2015
Earlier work this paper cites.
Tran, D., Bourdev, L., Fergus, R., Torresani, L., Paluri, M.: Learning spatiotemporal features with 3d convolutional networks. In: ICCV (2015)
2015
Earlier work this paper cites.
Yue-Hei Ng, J., Hausknecht, M., Vijayanarasimhan, S., Vinyals, O., Monga, R., Toderici, G.: Beyond short snippets: Deep networks for video classification. In: CVPR (2015)
2015
Earlier work this paper cites.
Feichtenhofer, C., Pinz, A., Zisserman, A.: Convolutional two-stream network fusion for video action recognition. In: CVPR (2016)
2016
Earlier work this paper cites.
He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR (2016)
2016
Earlier work this paper cites.
Wang, L., Xiong, Y., Wang, Z., Qiao, Y., Lin, D., Tang, X., Van Gool, L.: Temporal segment networks: Towards good practices for deep action recognition. In: ECCV (2016)
2016
Earlier work this paper cites.
Baker, B., Gupta, O., Naik, N., Raskar, R.: Designing neural network architectures using reinforcement learning. In: ICLR (2017)
2017
Earlier work this paper cites.
Carreira, J., Zisserman, A.: Quo vadis, action recognition? a new model and the kinetics dataset. In: CVPR (2017)
2017
Earlier work this paper cites.
Qiu, Z., Yao, T., Mei, T.: Learning spatio-temporal representation with pseudo-3d residual networks. In: ICCV (2017)
2017
Earlier work this paper cites.
Real, E., Moore, S., Selle, A., Saxena, S., Suematsu, Y.L., Tan, J., Le, Q.V., Kurakin, A.: Large-scale evolution of image classifiers. In: ICML (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: NeurIPS (2017)
2017
Cited alongside, same era.
Xie, L., Yuille, A.: Genetic cnn. In: ICCV (2017)
2017
Cited alongside, same era.
Zoph, B., Le, Q.V.: Neural architecture search with reinforcement learning. In: ICLR (2017)
2017
Cited alongside, same era.
2018
Cited alongside, same era.
Bello, I., Zoph, B., Vaswani, A., Shlens, J., Le, Q.V.: Attention augmented convolutional networks. In: ICCV (2019)
2019
Later among the works it cites.
Cao, S., Wang, X., Kitani, K.M.: Learnable embedding space for efficient neural architecture compression. In: ICLR (2019)
2019
Later among the works it cites.
Feichtenhofer, C., Fan, H., Malik, J., He, K.: Slowfast networks for video recognition. In: ICCV (2019)
2019
Later among the works it cites.
He, D., Zhou, Z., Gan, C., Li, F., Liu, X., Li, Y., Wang, L., Wen, S.: Stnet: Local and global spatial-temporal modeling for action recognition. In: AAAI (2019)
2019
Later among the works it cites.
Li, L., Talwalkar, A.: Random search and reproducibility for neural architecture search. In: UAI (2019)
2019
Later among the works it cites.
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Kandasamy, K., Neiswanger, W., Schneider, J., Poczos, B., Xing, E.P.: Neural architecture search with bayesian optimisation and optimal transport. In: NeurIPS (2018)
2018
Cited alongside, same era.
Liu, C., Zoph, B., Neumann, M., Shlens, J., Hua, W., Li, L.J., Fei-Fei, L., Yuille, A., Huang, J., Murphy, K.: Progressive neural architecture search. In: ECCV (2018)
2018
Cited alongside, same era.
Park, J., Woo, S., Lee, J.Y., Kweon, I.S.: Bam: Bottleneck attention module. In: BMVC (2018)
2018
Cited alongside, same era.
Wang, X., Girshick, R., Gupta, A., He, K.: Non-local neural networks. In: CVPR (2018)
2018
Cited alongside, same era.
Woo, S., Park, J., Lee, J.Y., So Kweon, I.: Cbam: Convolutional block attention module. In: ECCV (2018)
2018
Cited alongside, same era.
Xie, S., Sun, C., Huang, J., Tu, Z., Murphy, K.: Rethinking spatiotemporal feature learning: Speed-accuracy trade-offs in video classification. In: ECCV (2018)
2018
Cited alongside, same era.
Zhong, Z., Yan, J., Wu, W., Shao, J., Liu, C.L.: Practical block-wise neural network architecture generation. In: CVPR (2018)
2018
Cited alongside, same era.
Liu, C., Chen, L.C., Schroff, F., Adam, H., Hua, W., Yuille, A.L., Fei-Fei, L.: Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation. In: CVPR (2019)
2019
Later among the works it cites.
Liu, H., Simonyan, K., Yang, Y.: DARTS: Differentiable architecture search. In: ICLR (2019)
2019
Later among the works it cites.
Liu, X., Lee, J.Y., Jin, H.: Learning video representations from correspondence proposals. In: CVPR (2019)
2019
Later among the works it cites.
Monfort, M., Andonian, A., Zhou, B., Ramakrishnan, K., Bargal, S.A., Yan, T., Brown, L., Fan, Q., Gutfreund, D., Vondrick, C., et al.: Moments in time dataset: one million videos for event understanding. TPAMI (2019)
2019
Later among the works it cites.
Real, E., Aggarwal, A., Huang, Y., Le, Q.V.: Regularized evolution for image classifier architecture search. In: AAAI (2019)
2019
Later among the works it cites.
Xie, S., Kirillov, A., Girshick, R., He, K.: Exploring randomly wired neural networks for image recognition. In: ICCV (2019)
2019
Later among the works it cites.
Ryoo, M.S., Piergiovanni, A., Tan, M., Angelova, A.: Assemblenet: Searching for multi-stream neural connectivity in video architectures. In: ICLR (2020)
2020
Closest in time.
Stroud, J., Ross, D., Sun, C., Deng, J., Sukthankar, R.: D3d: Distilled 3d networks for video action recognition. In: WACV (2020)
2020
Closest in time.
Yu, K., Sciuto, C., Jaggi, M., Musat, C., Salzmann, M.: Evaluating the search phase of neural architecture search. In: ICLR (2020)
2020
Closest in time.