Ke Yu

I am currently a 3rd-year PhD candidate in the Multimedia Laboratory, The Chinese University of Hong Kong. My supervisor is Prof. Xiaoou Tang, and I work closely with Prof. Chen Change Loy and Prof. Chao Dong.

I got my B.Eng. degree in the Department of Electronic Engineering, Tsinghua University.

Email  /  Google Scholar  /  GitHub

I'm interested in image restoration, super-resolution and reinforcement learning.

Our EDVR wins the champions and outperforms the second place by a large margin in all four tracks in the NTIRE19 video restoration and enhancement challenges.

We propose Path-Restore, a multi-path CNN with a pathfinder that could dynamically select an appropriate route for each image region.

We propose Deep Network Interpolation (DNI), a simple yet universal approach to attain a smooth control of diverse imagery effects in many low-level vision tasks.

ESRGAN won the champion in the PIRM 2018 Challenge on Perceptual Super-Resolution (3rd track).

RL-Restore learns a policy to select appropriate tools from a toolbox to progressively restore the quality of a corrupted image.

We adopt Spatial Feature Transform (SFT) to generate affine transformation parameters for spatial-wise feature modulation, recovering textures faithful to semantic classes.

Fast AR-CNN achieves a speed up of 7.5x with almost no performance loss compared to ARCNN for compression artifacts reduction.

Thanks Jon Barron for sharing the website codes.