‪Liangyan Li‬ - ‪Google Scholar‬

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202120222023202416 15 54 17

Co-authors

Jun ChenElectrical and Computer Engineering, McMaster UniversityVerified email at mcmaster.ca
Huan LiuPh.D., Huawei Noah's Ark Lab, CanadaVerified email at huawei.com
Keyan WangXidian UniversityVerified email at mail.xidian.edu.cn
Muhammad AlrabeiahAssistant professor @ EE Dept., KSU, and AI and wireless tech consultant @ RIC, CSTVerified email at ksu.edu.sa
Da-ke HeGoogle Inc.Verified email at google.com

Liangyan Li

Liangyan Li

Ph.D. candidate at McMaster University

Verified email at mcmaster.ca - Homepage

Image Compression Machine Learning Dehazing


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
NTIRE 2021 challenge on quality enhancement of compressed video: Methods and results R Yang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	40	2021
Towards multi-domain single image dehazing via test-time training H Liu, Z Wu, L Li, S Salehkalaibar, J Chen, K Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022	38	2022
Persistent feature descriptors for video TY Muhammad Rabeiah M ALRABEIAH,Jun Chen,Dake He,Liangyan LI,Yingchan QIAO ... US Patent 10,534,964, 2020	12*	2020
SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge K Chen, L Li, H Liu, Y Li, C Tang, J Chen CVPR 2023 Workshop, 2023	7	2023
A Data-Centric Solution to NonHomogeneous Dehazing via Vision Transformer Y Liu, H Liu, L Li, Z Wu, J Chen CVPR 2023 Workshop, 2023	5	2023

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