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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…
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…
Learning in Audio-visual Context: A Review, Analysis, and New Perspective
Yake Wei, Di Hu, Yapeng Tian +1
Sight and hearing are two senses that play a vital role in human communication and scene understanding. To mimic human perception ability, audio-visual learning, aimed at developin…
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…
Learning to Answer Questions in Dynamic Audio-Visual Scenarios
Guangyao Li, Yake Wei, Yapeng Tian +3
In this paper, we focus on the Audio-Visual Question Answering (AVQA) task, which aims to answer questions regarding different visual objects, sounds, and their associations in vid…
Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution
Guangyuan Li, Jun Lv, Yapeng Tian +4
Magnetic resonance imaging (MRI) can present multi-contrast images of the same anatomical structures, enabling multi-contrast super-resolution (SR) techniques. Compared with SR rec…
Learning Spatio-Temporal Downsampling for Effective Video Upscaling
Xiaoyu Xiang, Yapeng Tian, Vijay Rengarajan +3
Downsampling is one of the most basic image processing operations. Improper spatio-temporal downsampling applied on videos can cause aliasing issues such as moiré patterns in space…
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…