62 citations · 100 across the 10 of their papers we have counts for
6 papers · 1 filter
Points2Polygons: Context-Based Segmentation from Weak Labels Using Adversarial Networks
Kuai Yu, Hakeem Frank, Daniel Wilson
In applied image segmentation tasks, the ability to provide numerous and precise labels for training is paramount to the accuracy of the model at inference time. However, this over…
Understanding Deformable Alignment in Video Super-Resolution
Kelvin C. K. Chan, Xintao Wang, Ke Yu +2
Deformable convolution, originally proposed for the adaptation to geometric variations of objects, has recently shown compelling performance in aligning multiple frames and is incr…
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
Xintao Wang, Kelvin C. K. Chan, Ke Yu +2
Video restoration tasks, including super-resolution, deblurring, etc, are drawing increasing attention in the computer vision community. A challenging benchmark named REDS is relea…
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…
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…