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Fangzhou HONG (洪方舟)

Ph.D. Student in MMLab@NTU

About Me

Fangzhou Hong is currently a first-year Ph.D. student in the School of Computer Science and Engineering at Nanyang Technological University (MMLab@NTU), supervised by Prof. Ziwei Liu. Previously, Fangzhou received his B.Eng. degree in Software Engineering from Tsinghua University in 2020. His research interests lie on the computer vision and deep learning. Particularly he is interested in 3D representation learning.

News
[Mar. 2021]

Two papers accepted to CVPR2021!

[Jan. 2021]

Start my journey in MMLab@NTU!

Publications
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LiDAR-based Panoptic Segmentation via Dynamic Shifting Network

Fangzhou Hong, Hui Zhou, Xinge Zhu, Hongsheng Li, Ziwei Liu

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021

[PDF] [Code]
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Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation

Xinge Zhu*, Hui Zhou*, Tai Wang, Fangzhou Hong, Yuexin Ma, Wei Li, Hongsheng Li, Dahua Lin

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 (Oral)

[PDF] [Code]
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LRC-Net: Learning Discriminative Features on Point Clouds by Encoding Local Region Contexts

Xinhai Liu, Zhizhong Han, Fangzhou Hong, Yu-Shen Liu, Matthias Zwicker

Computer Aided Geometric Design, 2020, 79: 101859. (SCI, 2017 Impact factor: 1.421, CCF B)

[PDF]
Education & Experiences
Nanyang Technological University
Singapore
Jan. 2021 - Present
Ph.D. Student in MMLab@NTU
The Chinese University of Hong Kong
Hong Kong, China
Jul. 2020 - Dec. 2020
Research Assistant in MMLab
SenseTime Group Limited
Beijing, China
Feb. 2019 - Dec. 2019
Research Intern
Tsinghua Unversity
Beijing, China
Aug. 2016 - Jun. 2020
Bachelor Degree in Software Engineering
Awards & Scholarships

Outstanding Undergraduate Thesis of Tsinghua University

2020

Outstanding Graduate of Tsinghua University

2020

Outstanding Graduate of Beijing

2020

Outstanding Graduate of School of Software, Tsinghua University

2020

ICBC Scholarship (Top 3%)

2019

Hua Wei Scholarship (Top 1%)

2018

Tung OOCL Scholarship (Top 5%)

2017