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20182022
most citedLAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond

38 citations · 78 across the 10 of their papers we have counts for

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15 papers · 1 filter

cs.CV2022

Mutual Guidance and Residual Integration for Image Enhancement

Kun Zhou, KenKun Liu, Wenbo Li +2

Previous studies show the necessity of global and local adjustment for image enhancement. However, existing convolutional neural networks (CNNs) and transformer-based models face g…

cs.CV20221 cited

Video Frame Interpolation with Transformer

Liying Lu, Ruizheng Wu, Huaijia Lin +2

Video frame interpolation (VFI), which aims to synthesize intermediate frames of a video, has made remarkable progress with development of deep convolutional networks over past yea…

cs.CV20221 cited

Exploring Motion Ambiguity and Alignment for High-Quality Video Frame Interpolation

Kun Zhou, Wenbo Li, Xiaoguang Han +1

For video frame interpolation (VFI), existing deep-learning-based approaches strongly rely on the ground-truth (GT) intermediate frames, which sometimes ignore the non-unique natur…

cs.CV20219 cited

MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution

Liying Lu, Wenbo Li, Xin Tao +2

Reference-based image super-resolution (RefSR) has shown promising success in recovering high-frequency details by utilizing an external reference image (Ref). In this task, textur…

cs.CV202138 cited

LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond

Wenbo Li, Kun Zhou, Lu Qi +3

Single image super-resolution (SISR) deals with a fundamental problem of upsampling a low-resolution (LR) image to its high-resolution (HR) version. Last few years have witnessed i…

cs.CV2021

Video Instance Segmentation with a Propose-Reduce Paradigm

Huaijia Lin, Ruizheng Wu, Shu Liu +2

Video instance segmentation (VIS) aims to segment and associate all instances of predefined classes for each frame in videos. Prior methods usually obtain segmentation for a frame…