ResearchTrend.AI
Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-Resolution

Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-Resolution

Yong Liu
Hang Dong
Boyang Liang
Song Liu
Qingji Dong
Kai Chen
Fangmin Chen
Lean Fu
Fei Wang
    ViT
ArXivPDFHTML

Papers citing "Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-Resolution"

4 / 4 papers shown
Title
CATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-Resolution
Xin Liu
Jie Liu
J. Tang
Gangshan Wu
SupR
ViT
54
0
0
10 Mar 2025
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr
Martin Danelljan
Radu Timofte
Namhyuk Ahn
Dongwoon Bai
...
Tongtong Zhao
Yuanbo Zhou
Haijie Zhuo
Ziyao Zong
Xueyi Zou
SupR
85
170
0
05 May 2020
Lightweight Image Super-Resolution with Information Multi-distillation Network
Lightweight Image Super-Resolution with Information Multi-distillation Network
Zheng Hui
Xinbo Gao
Yunchu Yang
Xiumei Wang
SupR
68
867
0
26 Sep 2019
Image-to-Image Translation with Conditional Adversarial Networks
Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola
Jun-Yan Zhu
Tinghui Zhou
Alexei A. Efros
SSeg
212
19,450
0
21 Nov 2016