11 code implementations • 7 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 #2 on Deblurring on REDS
no code implementations • 15 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.
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).
6 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.
1 code implementation • 21 Apr 2021 • Ren Yang, Radu Timofte, Jing Liu, Yi Xu, Xinjian Zhang, Minyi Zhao, Shuigeng Zhou, Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy, Xin Li, Fanglong Liu, He Zheng, Lielin Jiang, Qi Zhang, Dongliang He, Fu Li, Qingqing Dang, Yibin Huang, Matteo Maggioni, Zhongqian Fu, Shuai Xiao, Cheng Li, Thomas Tanay, Fenglong Song, Wentao Chao, Qiang Guo, Yan Liu, Jiang Li, Xiaochao Qu, Dewang Hou, Jiayu Yang, Lyn Jiang, Di You, Zhenyu Zhang, Chong Mou, Iaroslav Koshelev, Pavel Ostyakov, Andrey Somov, Jia Hao, Xueyi Zou, Shijie Zhao, Xiaopeng Sun, Yiting Liao, Yuanzhi Zhang, Qing Wang, Gen Zhan, Mengxi Guo, Junlin Li, Ming Lu, Zhan Ma, Pablo Navarrete Michelini, Hai Wang, Yiyun Chen, Jingyu Guo, Liliang Zhang, Wenming Yang, Sijung Kim, Syehoon Oh, Yucong Wang, Minjie Cai, Wei Hao, Kangdi Shi, Liangyan Li, Jun Chen, Wei Gao, Wang Liu, XiaoYu Zhang, Linjie Zhou, Sixin Lin, Ru Wang
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results.
3 code implementations • CVPR 2022 • 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.
Ranked #1 on Video Enhancement on MFQE v2
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).
1 code implementation • 9 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.
1 code implementation • CVPR 2022 • Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy
The diversity and complexity of degradations in real-world video super-resolution (VSR) pose non-trivial challenges in inference and training.
1 code implementation • 11 Apr 2022 • Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy
The exploitation of long-term information has been a long-standing problem in video restoration.
1 code implementation • 22 Jun 2022 • Shangchen Zhou, Kelvin C. K. Chan, Chongyi Li, Chen Change Loy
In this paper, we demonstrate that a learned discrete codebook prior in a small proxy space largely reduces the uncertainty and ambiguity of restoration mapping by casting blind face restoration as a code prediction task, while providing rich visual atoms for generating high-quality faces.
Ranked #1 on Blind Face Restoration on CelebA-Test
1 code implementation • 25 Jul 2022 • Jianyi Wang, Kelvin C. K. Chan, Chen Change Loy
Measuring the perception of visual content is a long-standing problem in computer vision.
Ranked #9 on Video Quality Assessment on MSU SR-QA Dataset
1 code implementation • 29 Jul 2022 • Kelvin C. K. Chan, Xiangyu Xu, Xintao Wang, Jinwei Gu, Chen Change Loy
While most existing perceptual-oriented approaches attempt to generate realistic outputs through learning with adversarial loss, our method, Generative LatEnt bANk (GLEAN), goes beyond existing practices by directly leveraging rich and diverse priors encapsulated in a pre-trained GAN.
1 code implementation • 19 Dec 2022 • Yuming Jiang, Kelvin C. K. Chan, Xintao Wang, Chen Change Loy, Ziwei Liu
To tackle these challenges, we propose C2-Matching in this work, which performs explicit robust matching crossing transformation and resolution.
2 code implementations • 23 Mar 2023 • Ziqi Huang, Tianxing Wu, Yuming Jiang, Kelvin C. K. Chan, Ziwei Liu
Specifically, we propose a novel relation-steering contrastive learning scheme to impose two critical properties of the relation prompt: 1) The relation prompt should capture the interaction between objects, enforced by the preposition prior.
no code implementations • 5 Apr 2023 • Xuhui Jia, Yang Zhao, Kelvin C. K. Chan, Yandong Li, Han Zhang, Boqing Gong, Tingbo Hou, Huisheng Wang, Yu-Chuan Su
This paper proposes a method for generating images of customized objects specified by users.
no code implementations • 14 Apr 2023 • Yu-Chuan Su, Kelvin C. K. Chan, Yandong Li, Yang Zhao, Han Zhang, Boqing Gong, Huisheng Wang, Xuhui Jia
Our approach greatly reduces the overhead for personalized image generation and is more applicable in many potential applications.
1 code implementation • CVPR 2023 • Ziqi Huang, Kelvin C. K. Chan, Yuming Jiang, Ziwei Liu
In this work, we present Collaborative Diffusion, where pre-trained uni-modal diffusion models collaborate to achieve multi-modal face generation and editing without re-training.
3 code implementations • 11 May 2023 • Jianyi Wang, Zongsheng Yue, Shangchen Zhou, Kelvin C. K. Chan, Chen Change Loy
We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution (SR).
1 code implementation • 14 Aug 2023 • Yu-Ju Tsai, Yu-Lun Liu, Lu Qi, Kelvin C. K. Chan, Ming-Hsuan Yang
Restoring facial details from low-quality (LQ) images has remained a challenging problem due to its ill-posedness induced by various degradations in the wild.
Ranked #2 on Blind Face Restoration on WIDER
1 code implementation • ICCV 2023 • Shangchen Zhou, Chongyi Li, Kelvin C. K. Chan, Chen Change Loy
We also propose a mask-guided sparse video Transformer, which achieves high efficiency by discarding unnecessary and redundant tokens.
Ranked #1 on Video Inpainting on YouTube-VOS 2018
no code implementations • 4 Dec 2023 • Xin Lin, Chao Ren, Kelvin C. K. Chan, Lu Qi, Jinshan Pan, Ming-Hsuan Yang
Multi-task image restoration has gained significant interest due to its inherent versatility and efficiency compared to its single-task counterpart.
no code implementations • 4 Dec 2023 • Yunhao Liu, Yu-Ju Tsai, Kelvin C. K. Chan, Xiangtai Li, Lu Qi, Ming-Hsuan Yang
Traditional heuristic approaches-either training models directly on these degraded images or their enhanced counterparts using face restoration techniques-have proven ineffective, primarily due to the degradation of facial features and the discrepancy in image domains.
no code implementations • 5 Dec 2023 • Shaoan Xie, Yang Zhao, Zhisheng Xiao, Kelvin C. K. Chan, Yandong Li, Yanwu Xu, Kun Zhang, Tingbo Hou
Our extensive experiments demonstrate the superior performance of our method in terms of visual quality, identity preservation, and text control, showcasing its effectiveness in the context of text-guided subject-driven image inpainting.
no code implementations • 3 Jan 2024 • Hexiang Hu, Kelvin C. K. Chan, Yu-Chuan Su, Wenhu Chen, Yandong Li, Kihyuk Sohn, Yang Zhao, Xue Ben, Boqing Gong, William Cohen, Ming-Wei Chang, Xuhui Jia
We introduce *multi-modal instruction* for image generation, a task representation articulating a range of generation intents with precision.
no code implementations • 17 Apr 2024 • Hao-Wei Chen, Yu-Syuan Xu, Kelvin C. K. Chan, Hsien-Kai Kuo, Chun-Yi Lee, Ming-Hsuan Yang
Towards this goal, we propose AdaIR, a novel framework that enables low storage cost and efficient training without sacrificing performance.
no code implementations • 2 May 2024 • Kelvin C. K. Chan, Yang Zhao, Xuhui Jia, Ming-Hsuan Yang, Huisheng Wang
In subject-driven text-to-image synthesis, the synthesis process tends to be heavily influenced by the reference images provided by users, often overlooking crucial attributes detailed in the text prompt.