I am a second-year master student in Robotics Institute at Carnegie Mellon University. I am now working on active learning and domain adaptation supervised by Prof. Fernando De la Torre and Prof. Shayok Chakraborty.

Previously, I received Bachelor of Science degree in Computer Science and Mathematics from Hong Kong University of Science and Technology with First Class Honors. I am honored to have worked with Prof. Chi-Keung Tang and Prof. Yu-Wing Tai in Hong Kong University of Science and Technology, Dr. Davide Modolo in AWS Rekognition team, Dr. Qi She in ByteDance, and Zhuyu Yao in MEGVII technology.

My research interests are computer vision and deep learning. Particularly, I am highly interested in solving real-world perception problems under low-labeling setting, which covers the topics of active learning, self-supervised learning, semi-supervised learning, few-shot learning, and their applications in image and video classification/detection.

I am applying for PhD starting from Fall 2023.

Email  /  Google Scholar  /  Github  /  LinkedIn

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(* indicates equal contribution)

Active Multi-target Domain Adaptation
On going ...
PatchML: Patch Based Learning for Multi-label Image Classification
Lin Zhang, Abhay Mittal, Ritwick Chaudhry, Kaustav Kundu, Davide Modolo
In submission to CVPR, 2023
Learning from Temporal Gradient for Semi-supervised Action Recognition
Junfei Xiao, Longlong Jing, Lin Zhang, Jie Hu, Qi She, Zongwei Zhou, Alan Yuille, Yingwei Li
CVPR, 2022
Inter-intra Variant Dual Representations for Self-supervised Video Recognition
Lin Zhang, Qi She, Zhengyang Shen, Changhu Wang
BMVC, 2021
project page / arXiv
MT-ORL: Multi-Task Occlusion Relationship Learning
Panhe Feng, Qi She, Lei Zhu, JiaXin Li, Lin ZHANG, Zijian Feng, Changhu Wang, Chunpeng Li, Xuejing Kang, Anlong Ming
ICCV, 2021
One-Shot Object Detection without Fine-Tuning
Lin Zhang*, Xiang Li* Yau Pun Chen, Yu-Wing Tai, Chi-Keung Tang
arxiv, 2020
project page / arXiv
Work Experiences
AWS Rekognition
May. 2022 - Aug. 2022 | Dr. Davide Modolo
ByteDance AI Lab
Feb. 2021 - Jun. 2021 | Dr. Qi She
Topic: self-supervised human action recognition
Jan. 2020 - Apr. 2020
Topic: object detection
HKUST Robotics Team
Nov. 2016 - Jul. 2017 | Prof. Kam-Tim Woo
Topic: camera-guided balance car design
Carnegie Mellon University
Master of Science in Computer Vision | Aug. 2021 - Dec. 2022(Expected)
Hong Kong University of Science and Technology
Bachelor of Science in Computer Science and Mathematics | Sep. 2016 - Jun. 2020 | GPA: 3.96/4.30
ETH Zurich
Undergraduate Exchange in Computer Science | Sep. 2018 - Jun. 2019
NeRF Speedup at Test Time via Super-resolution
Lin Zhang, Qifeng Chen

Train a super-resolution model on low-high resolution pairs generated by NeRF to accelerate NeRF generation at test time

Video Interpolation and Extrapolation in Long Intervals
Lin Zhang, Yu-Wing Tai, Chi-Keung Tang
slides / videos

Joint video interpolation and extrapolation on Cityscape dataset within long time intervals

Duplicate Question Detection
Lin Zhang, Dit-Yan Yeung
tech report

Detect duplicate questions on Quora dataset using RNN sequential models and autoencoder-generated augmented data

Analytics and Recommendation for User Location Data
Lin Zhang, Zijian Huang Gary Shueng Han CHAN
tech report

Designed and built an indoor localization system with Android devices, beacons, database and web development.