Can Zhang | SOC, NUS

Welcome!

I am currently a Ph.D. Candidate at the Department of Computer Science at the National University of Singapore (NUS), under the supervision of Prof. Gim Hee Lee.

Research Interests

My research interests lie broadly in the field of computer vision (CV), machine learning (ML). Specifically, my work explores the following areas:

3D scene understanding
Domain adaptation
Semi-, Un- and Self-supervised learning
Multi/Cross-modal learning
but not limited to.

News

[Jul. 2023] Get on domain adaptation is accepted to ICCV 2023.
[Jul. 2023] DG-UCDIR on cross-domain image retrieval is accepted to ICCV 2023.
[Mar. 2022] Miss on CTR prediction is accepted to ICDE 2022.
[May. 2022] CA-UDA on domain adaptation is available on arXiv.
[Oct. 2020] MPSD on surface defection is accepted to ICPR 2020.
[Oct. 2020] MSPAC on RGB-Infrared person re-identification is accepted to ICPR 2020.
[May 2020] MBCN on recommendation is accepted to SIGIR 2020.

Research

GeT: Generative Target Structure Debiasing for Domain Adaptation

Can Zhang, Gim Hee Lee

ICCV, 2023

PDF Project page Code
Unsupervised Feature Representation Learning for Domain-generalized Cross-domain Image Retrieval

Conghui Hu, Can Zhang, Gim Hee Lee

ICCV, 2023

PDF Project page Code
Miss: Multi-interest self-supervised learning framework for click-through rate prediction

Wei Guo*, Can Zhang*, Zhicheng He*, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang (*co-first)

ICDE, 2022

PDF Project page Code
CA-UDA: Class-Aware Unsupervised Domain Adaptation with Optimal Assignment and Pseudo-Label Refinement

Can Zhang, Gim Hee Lee

arXiv, 2022

PDF Project page Code Demo
Multi-Scale Cascading Network with Compact Feature Learning for RGB-Infrared Person Re-Identification

Can Zhang, Hong Liu, Wei Guo, Mang Ye

ICPR, 2020

PDF
Mobile Phone Surface Defect Detection Based on Improved Faster R-CNN

Tao Wang, Can Zhang, Runwei Ding, Ge Yang

ICPR, 2020

PDF
Multi-Branch Convolutional Network for Context-Aware Recommendation

Wei Guo*, Can Zhang*, Huifeng Guo, Ruiming Tang, Xiuqiang He (*co-first)

SIGIR, 2020

PDF

Awards and Honors

National Scholarship, 2017
National Scholarship, 2016
National Scholarship, 2015
Outstanding Freshmen Scholarship, WHU, 2014

Teaching Assistant

2018/2019 Semester 1: Scientific Quality and Research Methods, PKU
2020/2021 Semester 1: CS5340 Uncertainty Modelling in AI, NUS
2020/2021 Semester 2: CS5477 3D Computer Vision, NUS
2021/2022 Semester 1: CS5340 Uncertainty Modelling in AI, NUS

Services

Conference reviewers: CVPR, ICME, NeurIPS, ICLR