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A Dual-scale Lead-seperated Transformer With Lead-orthogonal Attention And Meta-information For Ecg Classification
Yang Li, Guijin Wang, Zhourui Xia +2
Auxiliary diagnosis of cardiac electrophysiological status can be obtained through the analysis of 12-lead electrocardiograms (ECGs). This work proposes a dual-scale lead-separated…
Knowledge Distillation based Degradation Estimation for Blind Super-Resolution
Bin Xia, Yulun Zhang, Yitong Wang +4
Blind image super-resolution (Blind-SR) aims to recover a high-resolution (HR) image from its corresponding low-resolution (LR) input image with unknown degradations. Most of the e…
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…
Basic Binary Convolution Unit for Binarized Image Restoration Network
Bin Xia, Yulun Zhang, Yitong Wang +4
Lighter and faster image restoration (IR) models are crucial for the deployment on resource-limited devices. Binary neural network (BNN), one of the most promising model compressio…
Meta-Learning based Degradation Representation for Blind Super-Resolution
Bin Xia, Yapeng Tian, Yulun Zhang +3
The most of CNN based super-resolution (SR) methods assume that the degradation is known (\eg, bicubic). These methods will suffer a severe performance drop when the degradation is…
Structured Sparsity Learning for Efficient Video Super-Resolution
Bin Xia, Jingwen He, Yulun Zhang +4
The high computational costs of video super-resolution (VSR) models hinder their deployment on resource-limited devices, (e.g., smartphones and drones). Existing VSR models contain…
SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonization
Yucheng Hang, Bin Xia, Wenming Yang +1
Image harmonization aims to achieve visual consistency in composite images by adapting a foreground to make it compatible with a background. However, existing methods always only u…
STDAN: Deformable Attention Network for Space-Time Video Super-Resolution
Hai Wang, Xiaoyu Xiang, Yapeng Tian +2
The target of space-time video super-resolution (STVSR) is to increase the spatial-temporal resolution of low-resolution (LR) and low frame rate (LFR) videos. Recent approaches bas…
Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-Resolution
Bin Xia, Yapeng Tian, Yucheng Hang +3
Reference-based super-resolution (RefSR) has made significant progress in producing realistic textures using an external reference (Ref) image. However, existing RefSR methods obta…
Efficient Non-Local Contrastive Attention for Image Super-Resolution
Bin Xia, Yucheng Hang, Yapeng Tian +3
Non-Local Attention (NLA) brings significant improvement for Single Image Super-Resolution (SISR) by leveraging intrinsic feature correlation in natural images. However, NLA gives…
RFormer: Transformer-based Generative Adversarial Network for Real Fundus Image Restoration on A New Clinical Benchmark
Zhuo Deng, Yuanhao Cai, Lu Chen +6
Ophthalmologists have used fundus images to screen and diagnose eye diseases. However, different equipments and ophthalmologists pose large variations to the quality of fundus imag…