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Shanxin Yuan
Shanxin Yuan is a Senior Research Scientist in Computer Vision for Huawei Technologies Research and Development, UK. He received the PhD degree from Imperial College London, the MSc degree from the University of Chinese Academy of Sciences, and the BSc degree from China Agricultural University. His research interests are machine learning and computer vision, he has beening working on hand pose estimation and low-level vision. He was co-organizer of NTIRE 2020 workshop along with CVPR 2020 and AIM 2019 workshop along with ICCV 2019. He was the lead organizer of the HIM2017 challenge along with the HANDS17 workshop along with ICCV 2017. He regularly reviews for major computer vision conferences (CVPR, ICCV, ECCV, and NeurIPS) and related journals (TPAMI, IJCV and TIP).
Email /
Google Scholar /
Github /
Linkedin
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Research
My research interests are machine learning and computer vision. I have been working on hand pose estimation and low-level vision.
I am looking for research interns and contractors in computer vision and machine learning, feel free to contact me if you are interested.
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Self-Adaptively Learning to Demoiré from Focused and Defocused Image Pairs
L Liu,
S Yuan,
J Liu,
L Bao,
G Slabaugh,
Q Tian
NeurIPS, 2020
Paper /
arXiv /
Project page
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Wavelet-Based Dual-Branch Network for Image Demoireing
L Liu,
J Liu,
S Yuan,
G Slabaugh,
A Leonardis,
W Zhou,
Q Tian
ECCV, 2020
Paper /
arXiv
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NTIRE 2020 Challenge on Image Demoireing: Methods and Results
S Yuan,
R Timofte,
A Leonardis,
G Slabaugh,
et al.
CVPRW, 2020
Paper/
arXiv/
NTIRE 2020/
CodaLab
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Video Super-resolution with Temporal Group Attention
T Isobe,
S Li,
X Jia,
S Yuan,
G Slabaugh,
C Xu,
YL Li,
S Wang,
Q Tian
CVPR, 2020
Paper/
arXiv/
Code
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Image Demoireing with Learnable Bandpass Filters
B Zheng,
S Yuan,
G Slabaugh,
A Leonardis
CVPR, 2020
Paper/
arXiv/
Code
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Aim 2019 challenge on image demoireing: Methods and results
S Yuan,
R Timofte,
G Slabaugh,
A Leonardis,
B Zheng,
X Ye,
X Tian,
Y Chen,
X Cheng,
Z Fu,
J Yang,
M Hong,
W Lin,
W Yang,
Y Qu,
H-K Shin,
J-Y Kim,
S-J Ko,
H Dong,
Y Guo,
J Wang,
X Ding,
Z Han,
S Dipta Das,
K Purohit,
P Kandula,
M Suin,
AN Rajagopalan
ICCVW, 2019
Paper/
arXiv/
AIM 2019/
CodaLab
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Aim 2019 challenge on image demoireing: Dataset and study
S Yuan,
R Timofte,
G Slabaugh,
A Leonardis
ICCVW, 2019
Paper/
arXiv/
AIM 2019/
CodaLab
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3D Hand Pose Estimation from RGB Using Privileged Learning with Depth Data
S Yuan,
B Stenger,
T-K Kim
ICCVW, 2019
Paper/
arXiv
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Opening the Black Box: Hierarchical Sampling Optimization for Estimating Human Hand Pose
D Tang,
Q Ye,
S Yuan,
T Taylor,
P Kohli,
C Keskin,
T-K Kim,
J Shotton
TPAMI, 2018
Paper
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Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
S Yuan,
G Garcia-Hernando,
B Stenger,
G Moon,
J-Y Chang,
K-M Lee,
P Molchanov,
J Kautz,
S Honari,
L Ge,
J Yuan,
X Chen,
G Wang,
F Yang,
K Akiyama,
Y Wu,
Q Wan,
M Madadi,
S Escalera,
S Li,
D Lee,
I Oikonomidis,
A Argyros,
T-K Kim
CVPR, 2018
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First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations
G Garcia-Hernando,
S Yuan,
S Baek,
T-K Kim,
CVPR, 2018
Paper
arXiv
Website
Data
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The 2017 Hands in the Million Challenge on 3D Hand Pose Estimation
S Yuan,
Q Ye,
G Garcia-Hernando,
T-K Kim
arXiv, 2017
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BigHand2.2M Benchmark: Hand Pose Data Set and State of the Art Analysis
S Yuan,
Q Ye,
B Stenger,
S Jain,
T-K Kim
CVPR, 2017
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Spatial Attention Deep Net with Partial PSO for Hierarchical Hybrid Hand Pose Estimation
Q Ye,
S Yuan,
T-K Kim
ECCV, 2016
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Co-organizer, NTIRE 2020
Co-organizer, HIM 2017
Co-organizer, AIM 2019
Reviewer, CVPR, NeurIPS, ICCV, ECCV
Reviewer, TPAMI, IJCV, TIP
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