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Hengyuan Zhao

Researcher at Chinese Academy of Sciences

Publications -  10
Citations -  421

Hengyuan Zhao is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Computer science & Pixel. The author has an hindex of 5, co-authored 10 publications receiving 94 citations. Previous affiliations of Hengyuan Zhao include Nanjing University of Posts and Telecommunications.

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Efficient Image Super-Resolution Using Pixel Attention

TL;DR: This work designs a lightweight convolutional neural network for image super resolution with a newly proposed pixel attention scheme that could achieve similar performance as the lightweight networks - SRResNet and CARN, but with only 272K parameters.
Proceedings ArticleDOI

ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic

TL;DR: Wang et al. as discussed by the authors proposed a new solution pipeline that combines classification and SR in a unified framework, which can help most existing methods (e.g., FSRCNN, CARN, SRResNet, RCAN) save up to 50% FLOPs on DIV8K datasets.
Book ChapterDOI

Efficient Image Super-Resolution Using Pixel Attention

TL;DR: Zhao et al. as discussed by the authors designed a lightweight convolutional neural network with a pixel attention scheme, which produces 3D attention maps instead of a 1D attention vector or a 2D map.
Book ChapterDOI

AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results

Kai Zhang, +77 more
TL;DR: The AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results as discussed by the authors was held in 2019, where the goal was to devise a network that reduces one or several aspects such as runtime, parameter count, FLOPs, activations, and memory consumption.