Search Results for author: Kelvin C. K. Chan

Found 8 papers, 5 papers with code

Temporally Consistent Video Colorization with Deep Feature Propagation and Self-regularization Learning

no code implementations9 Oct 2021 Yihao Liu, Hengyuan Zhao, Kelvin C. K. Chan, Xintao Wang, Chen Change Loy, Yu Qiao, Chao Dong

We address this problem from a new perspective, by jointly considering colorization and temporal consistency in a unified framework.

Colorization

Robust Reference-based Super-Resolution via C2-Matching

1 code implementation CVPR 2021 Yuming Jiang, Kelvin C. K. Chan, Xintao Wang, Chen Change Loy, Ziwei Liu

However, performing local transfer is difficult because of two gaps between input and reference images: the transformation gap (e. g. scale and rotation) and the resolution gap (e. g. HR and LR).

Super-Resolution

BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment

1 code implementation27 Apr 2021 Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy

We show that by empowering the recurrent framework with the enhanced propagation and alignment, one can exploit spatiotemporal information across misaligned video frames more effectively.

Video Enhancement Video Restoration +1

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

4 code implementations CVPR 2021 Kelvin C. K. Chan, Xintao Wang, Ke Yu, Chao Dong, Chen Change Loy

Video super-resolution (VSR) approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension.

Video Super-Resolution

GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution

no code implementations CVPR 2021 Kelvin C. K. Chan, Xintao Wang, Xiangyu Xu, Jinwei Gu, Chen Change Loy

We show that pre-trained Generative Adversarial Networks (GANs), e. g., StyleGAN, can be used as a latent bank to improve the restoration quality of large-factor image super-resolution (SR).

GAN inversion Image Super-Resolution

Understanding Deformable Alignment in Video Super-Resolution

no code implementations15 Sep 2020 Kelvin C. K. Chan, Xintao Wang, Ke Yu, Chao Dong, Chen Change Loy

Aside from the contributions to deformable alignment, our formulation inspires a more flexible approach to introduce offset diversity to flow-based alignment, improving its performance.

Optical Flow Estimation Video Super-Resolution

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

8 code implementations7 May 2019 Xintao Wang, Kelvin C. K. Chan, Ke Yu, Chao Dong, Chen Change Loy

In this work, we propose a novel Video Restoration framework with Enhanced Deformable networks, termed EDVR, to address these challenges.

 Ranked #1 on Deblurring on REDS

Deblurring Video Restoration +1

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