1.2k citations · 1.8k across the 51 of their papers we have counts for
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Mitigating Artifacts in Real-World Video Super-Resolution Models
Liangbin Xie, Xintao Wang, Shuwei Shi +3
The recurrent structure is a prevalent framework for the task of video super-resolution, which models the temporal dependency between frames via hidden states. When applied to real…
Cross Aggregation Transformer for Image Restoration
Zheng Chen, Yulun Zhang, Jinjin Gu +3
Recently, Transformer architecture has been introduced into image restoration to replace convolution neural network (CNN) with surprising results. Considering the high computationa…
Self-Supervised Intensity-Event Stereo Matching
Jinjin Gu, Jinan Zhou, Ringo Sai Wo Chu +5
Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption. Despite t…
Efficient Image Super-Resolution using Vast-Receptive-Field Attention
Lin Zhou, Haoming Cai, Jinjin Gu +5
The attention mechanism plays a pivotal role in designing advanced super-resolution (SR) networks. In this work, we design an efficient SR network by improving the attention mechan…
Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images
Jinjin Gu, Haoming Cai, Chenyu Dong +4
Rendering high-resolution (HR) graphics brings substantial computational costs. Efficient graphics super-resolution (SR) methods may achieve HR rendering with small computing resou…
Accurate Image Restoration with Attention Retractable Transformer
Jiale Zhang, Yulun Zhang, Jinjin Gu +3
Recently, Transformer-based image restoration networks have achieved promising improvements over convolutional neural networks due to parameter-independent global interactions. To…
Rethinking Alignment in Video Super-Resolution Transformers
Shuwei Shi, Jinjin Gu, Liangbin Xie +3
The alignment of adjacent frames is considered an essential operation in video super-resolution (VSR). Advanced VSR models, including the latest VSR Transformers, are generally equ…
NTIRE 2022 Challenge on Perceptual Image Quality Assessment
Jinjin Gu, Haoming Cai, Chao Dong +2
This paper reports on the NTIRE 2022 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (…
Blueprint Separable Residual Network for Efficient Image Super-Resolution
Zheyuan Li, Yingqi Liu, Xiangyu Chen +4
Recent advances in single image super-resolution (SISR) have achieved extraordinary performance, but the computational cost is too heavy to apply in edge devices. To alleviate this…
Evaluating the Generalization Ability of Super-Resolution Networks
Yihao Liu, Hengyuan Zhao, Jinjin Gu +2
Performance and generalization ability are two important aspects to evaluate the deep learning models. However, research on the generalization ability of Super-Resolution (SR) netw…
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…