29. どこが強いのか
The Chinese University of Hong Kong
◦ SRCNNの著者のChao Dongがいた研究機関
◦ 今も⼀緒に⾊々やってる
◦ CUHK-SenseTime Joint Lab なるものが…
◦ ECCV2018のPIRMチャレンジでも優勝した模様
◦ ゲームのテクスチャを超解像して話題になったやつ
Twitter
◦ ESPCN & SRGANの発表
ETH Zurich
◦ Low-level vision全般に強い
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33. ⽂献⼀覧
[1] Dong, Chao, et al. "Learning a deep convolutional network for image super-resolution." Europeanconference on computer vision. Springer, Cham, 2014.
[2] Kim, Jiwon, Jung Kwon Lee, and Kyoung Mu Lee. "Accurate image super-resolution using very deep convolutional networks." Proceedings of the IEEE conference on computer vision and pattern recognition.
2016.
[3] Dong, Chao, Chen Change Loy, and XiaoouTang. "Accelerating the super-resolution convolutional neural network." European conference on computer vision. Springer, Cham, 2016.
[4] Shi, Wenzhe, et al. "Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network." Proceedings of the IEEE conference on computer vision and pattern
recognition. 2016.
[5] Ledig, Christian, et al. "Photo-realistic single image super-resolution using a generative adversarial network." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.
[6] Blau, Yochai, and Tomer Michaeli. "The perception-distortion tradeoff." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018.
[7] Lim, Bee, et al. "Enhanced deep residual networks for single image super-resolution." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2017.
[8] Lai, Wei-Sheng, et al. "Deep laplacian pyramid networks for fast and accurate super-resolution." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.
[9]Zhang, Yulun, et al. "Residual dense network for image super-resolution." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018.
[10] Haris, Muhammad, Gregory Shakhnarovich, and Norimichi Ukita. "Deep back-projection networks for super-resolution." Proceedings of the IEEE conference on computer vision and pattern recognition. 2018.
[11] Zhang, Yulun, et al. "Image super-resolution using very deep residual channel attention networks." Proceedings of the EuropeanConference on Computer Vision (ECCV). 2018.
[12] Nagano, Yudai, and Yohei Kikuta. "SRGAN for super-resolving low-resolution food images." Proceedings of the Joint Workshop on Multimedia for Cooking and Eating Activities and Multimedia Assisted Dietary
Management. ACM, 2018.
[13] Timofte, Radu, Rasmus Rothe, and Luc VanGool. "Seven ways to improve example-based single image super resolution." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
2016.
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