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Robust Video Super-Resolution with Learned Temporal Dynamics.

, , , , , , and . ICCV, page 2526-2534. IEEE Computer Society, (2017)

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Reshaping deep neural network for fast decoding by node-pruning., , , , and . ICASSP, page 245-249. IEEE, (2014)An Empirical Investigation of Efficient Spatio-Temporal Modeling in Video Restoration., , , and . CVPR Workshops, page 0. Computer Vision Foundation / IEEE, (2019)Development of the 2012 SJTU HVR system., , and . ICMI, page 539-544. ACM, (2012)TTS synthesis with bidirectional LSTM based recurrent neural networks., , , and . INTERSPEECH, page 1964-1968. ISCA, (2014)Balanced Two-Stage Residual Networks for Image Super-Resolution., , , , , , , , and . CVPR Workshops, page 1157-1164. IEEE Computer Society, (2017)NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results., , , , , , , , , and 50 other author(s). CVPR Workshops, page 1985-1995. Computer Vision Foundation / IEEE, (2019)On the training aspects of Deep Neural Network (DNN) for parametric TTS synthesis., , , and . ICASSP, page 3829-3833. IEEE, (2014)Multi-speaker modeling and speaker adaptation for DNN-based TTS synthesis., , , and . ICASSP, page 4475-4479. IEEE, (2015)YouTube-VOS: Sequence-to-Sequence Video Object Segmentation., , , , , , , , and . ECCV (5), volume 11209 of Lecture Notes in Computer Science, page 603-619. Springer, (2018)YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark., , , , , , and . CoRR, (2018)