activity
20202022
most citedReal-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

85 citations · 93 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV20221 cited

VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution

Liangbin Xie. Xintao Wang, Honglun Zhang, Chao Dong +1

Most of the existing video face super-resolution (VFSR) methods are trained and evaluated on VoxCeleb1, which is designed specifically for speaker identification and the frames in…

cs.CV2022

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Meisong Zheng +75

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…

eess.IV202185 cited

Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

Xintao Wang, Liangbin Xie, Chao Dong +1

Though many attempts have been made in blind super-resolution to restore low-resolution images with unknown and complex degradations, they are still far from addressing general rea…

cs.CV20212 cited

Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution

Liangbin Xie, Xintao Wang, Chao Dong +2

Recent blind super-resolution (SR) methods typically consist of two branches, one for degradation prediction and the other for conditional restoration. However, our experiments sho…

cs.CV20205 cited

Enhanced Quadratic Video Interpolation

Yihao Liu, Liangbin Xie, Li Siyao +3

With the prosperity of digital video industry, video frame interpolation has arisen continuous attention in computer vision community and become a new upsurge in industry. Many lea…