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20192023
most citedLearning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising

50 citations · 170 across the 13 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CV2021

BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment

Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu +1

A recurrent structure is a popular framework choice for the task of video super-resolution. The state-of-the-art method BasicVSR adopts bidirectional propagation with feature align…

eess.IV2021

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…

cs.CV2021★ 4 cited

3D Human Pose, Shape and Texture from Low-Resolution Images and Videos

Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer +2

3D human pose and shape estimation from monocular images has been an active research area in computer vision. Existing deep learning methods for this task rely on high-resolution i…

cs.CV2021★ 4 cited

Exploiting Raw Images for Real-Scene Super-Resolution

Xiangyu Xu, Yongrui Ma, Wenxiu Sun +1

Super-resolution is a fundamental problem in computer vision which aims to overcome the spatial limitation of camera sensors. While significant progress has been made in single ima…

cs.CV2021★ 50 cited

Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising

Xiangyu Xu, Muchen Li, Wenxiu Sun +1

Existing denoising methods typically restore clear results by aggregating pixels from the noisy input. Instead of relying on hand-crafted aggregation schemes, we propose to explici…