2 citations · 2 across the 5 of their papers we have counts for
5 papers
Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domain
Qunliang Xing, Mai Xu, Shengxi Li +4
Existing quality enhancement methods for compressed images focus on aligning the enhancement domain with the raw domain to yield realistic images. However, these methods exhibit a…
Lightweight network towards real-time image denoising on mobile devices
Zhuoqun Liu, Meiguang Jin, Ying Chen +3
Deep convolutional neural networks have achieved great progress in image denoising tasks. However, their complicated architectures and heavy computational cost hinder their deploym…
SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancement
Canqian Yang, Meiguang Jin, Yi Xu +3
Image-adaptive lookup tables (LUTs) have achieved great success in real-time image enhancement tasks due to their high efficiency for modeling color transforms. However, they embed…
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…
Progressive Training of A Two-Stage Framework for Video Restoration
Meisong Zheng, Qunliang Xing, Minglang Qiao +4
As a widely studied task, video restoration aims to enhance the quality of the videos with multiple potential degradations, such as noises, blurs and compression artifacts. Among v…