Learning-Based Multi-Frame Video Quality Enhancement

IEEE 2019 ICIP presentation learning-based multi-frame video quality enhancement visionular This paper was presented by Junchao Tong, Xilin Wu, Dandan Ding, Zheng Zhu, and Zoe Liu, “Learning-Based Multi-Frame Video Quality Enhancement,” in the Proceedings of the IEEE International Conference on Image Processing (ICIP), September 22-25, 2019 in Taipei, Taiwan. The convolution neural network (CNN) has shown great success in video quality enhancement. Existing methods mainly conduct enhancement tasks in the spatial domain, exploring the pixel correlations within one frame. Taking advantage of the similarity across successive frames, this paper demonstrates a learning-based multi-frame approach, with an aim to explore the greatest potential for video quality...

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