51 citations · 129 across the 14 of their papers we have counts for
14 papers
Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning
Haoyu Chen, Wenbo Li, Jinjin Gu +6
For image super-resolution (SR), bridging the gap between the performance on synthetic datasets and real-world degradation scenarios remains a challenge. This work introduces a nov…
CoSeR: Bridging Image and Language for Cognitive Super-Resolution
Haoze Sun, Wenbo Li, Jianzhuang Liu +5
Existing super-resolution (SR) models primarily focus on restoring local texture details, often neglecting the global semantic information within the scene. This oversight can lead…
AsConvSR: Fast and Lightweight Super-Resolution Network with Assembled Convolutions
Jiaming Guo, Xueyi Zou, Yuyi Chen +4
In recent years, videos and images in 720p (HD), 1080p (FHD) and 4K (UHD) resolution have become more popular for display devices such as TVs, mobile phones and VR. However, these…
A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolution
Hengsheng Zhang, Xueyi Zou, Jiaming Guo +3
Online processing of compressed videos to increase their resolutions attracts increasing and broad attention. Video Super-Resolution (VSR) using recurrent neural network architectu…
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Xin Li +49
This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compress…
Adaptive Local Implicit Image Function for Arbitrary-scale Super-resolution
Hongwei Li, Tao Dai, Yiming Li +2
Image representation is critical for many visual tasks. Instead of representing images discretely with 2D arrays of pixels, a recent study, namely local implicit image function (LI…
Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restoration
Jing Lin, Xiaowan Hu, Yuanhao Cai +5
How to properly model the inter-frame relation within the video sequence is an important but unsolved challenge for video restoration (VR). In this work, we propose an unsupervised…
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…
Flow-Guided Sparse Transformer for Video Deblurring
Jing Lin, Yuanhao Cai, Xiaowan Hu +7
Exploiting similar and sharper scene patches in spatio-temporal neighborhoods is critical for video deblurring. However, CNN-based methods show limitations in capturing long-range…
Locally Adaptive Structure and Texture Similarity for Image Quality Assessment
Keyan Ding, Yi Liu, Xueyi Zou +2
The latest advances in full-reference image quality assessment (IQA) involve unifying structure and texture similarity based on deep representations. The resulting Deep Image Struc…
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
Goutam Bhat, Martin Danelljan, Radu Timofte +25
This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times hig…
NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results
Ren Yang, Radu Timofte, Jing Liu +69
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Di…
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei, Hannan Lu, Radu Timofte +68
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…
Unsupervised Image Super-Resolution with an Indirect Supervised Path
Zhen Han, Enyan Dai, Xu Jia +5
The task of single image super-resolution (SISR) aims at reconstructing a high-resolution (HR) image from a low-resolution (LR) image. Although significant progress has been made b…