128 citations · 877 across the 52 of their papers we have counts for
4 papers · 1 filter
Deep Network Interpolation for Continuous Imagery Effect Transition
Xintao Wang, Ke Yu, Chao Dong +2
Deep convolutional neural network has demonstrated its capability of learning a deterministic mapping for the desired imagery effect. However, the large variety of user flavors mot…
Improving On-policy Learning with Statistical Reward Accumulation
Yubin Deng, Ke Yu, Dahua Lin +2
Deep reinforcement learning has obtained significant breakthroughs in recent years. Most methods in deep-RL achieve good results via the maximization of the reward signal provided…
Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning
Ke Yu, Chao Dong, Liang Lin +1
We investigate a novel approach for image restoration by reinforcement learning. Unlike existing studies that mostly train a single large network for a specialized task, we prepare…
Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform
Xintao Wang, Ke Yu, Chao Dong +1
Despite that convolutional neural networks (CNN) have recently demonstrated high-quality reconstruction for single-image super-resolution (SR), recovering natural and realistic tex…