Homepage - Haidong Zhu

Haidong Zhu

I am currently pursuing my Ph.D. in the Department of Computer Science at the University of Southern California (USC). I completed my Bachelor's Degree in Electronic Engineering from Tsinghua University in 2019. As a Research Assistant/Teaching Assistant, I have the privilege of working at the USC IRIS Computer Vision Lab, advised by Prof. Ram Nevatia.

My research interests lie in computer vision and deep learning, especially multimodal analysis for 3-D vision and biometric understanding.

Email / Resume / one-page CV / Github / Google Scholar

Education

University of Southern California, CA, USA
Ph.D. • Aug. 2019 to May 2024
Department of Computer Science

Tsinghua University, Beijing, China
B.Eng. • Sep. 2015 to Jul. 2019
Department of Electronic Engineering

Experiences

IRIS Computer Vision Lab, University of Southern California, Los Angeles, CA
Research Assistant • Aug. 2019 to May 2024
Advisor: Professor Ram Nevatia

Applied Sciences Group, Microsoft, Redmond, WA
Research Intern • May. 2023 to Aug. 2023
Mentor: Dr. Tianyu Ding

Lab 126, Amazon, Bellevue, WA
Applied Scientist Intern • May. 2022 to Aug. 2022
Mentor: Dr. Yuyin Sun

AI Lab, Bytedance Inc., Mountain View, CA
Research Intern • May. 2021 to Aug. 2021
Mentor: Dr. Ye Yuan

Visual Computing Group, Harvard University, Cambridge, MA
Undergraduate Research Intern • July. 2018 to Sept. 2018
Advisor: Professor Hanspeter Pfister

Multimedia Signal and Intelligent Information Processing Laboratory, Tsinghua University, Beijing, China
Research Assistant • Nov. 2018 to Jun. 2019
Advisor: Professor Ji Wu

i-Vision Group, Tsinghua University, Beijing, China
Research Assistant • Feb. 2018 to Apr. 2019
Advisor: Professor Jiwen Lu

Information Cognition & Intelligent System Lab, Tsinghua University, Beijing, China
Research Assistant • May 2017 to Feb. 2018
Advisor: Professor Jiansheng Chen

Preprint

	CaesarNeRF: Calibrated Semantic Representation for Few-Shot Generalizable Neural Rendering Haidong Zhu, Tianyu Ding, Tianyi Chen, Ilya Zharkov, Ram Nevatia, and Luming Liang [Paper] [Supp] [Project]
	The Efficiency Spectrum of Large Language Models: An Algorithmic Survey Tianyu Ding, Tianyi Chen, Haidong Zhu, Jiachen Jiang, Yiqi Zhong, Jinxin Zhou, Guangzhi Wang, Zhihui Zhu, Ilya Zharkov, and Luming Liang [Paper] [Project]

Selected Manuscripts

	SEAS: ShapE-Aligned Supervision for Person Re-Identification Haidong Zhu, Pranav Budhwant, Zhaoheng Zheng, and Ram Nevatia Accetped to IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024 [Paper (TBA)]
	Large Language Models are Good Prompt Learners for Low-Shot Image Classification Zhaoheng Zheng, Jingmin Wei, Xuefeng Hu, Haidong Zhu, and Ram Nevatia Accetped to IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024 [Paper] [Code]
	ShARc: Shape and Appearance ReCognition for Person Identification In-the-Wild Haidong Zhu, Wanrong Zheng, Zhaoheng Zheng, and Ram Nevatia In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 6290-6300, 2024 [Paper]
	CAILA: Concept-Aware Intra-Layer Adapters for Compositional Zero-Shot Learning Zhaoheng Zheng, Haidong Zhu, and Ram Nevatia In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 1721-1731, 2024 [Paper] [Code]
	GaitRef: Gait Recognition with Refined Sequential Skeletons Haidong Zhu, Wanrong Zheng, Zhaoheng Zheng, and Ram Nevatia In Proceedings of IEEE International Joint Conference on Biometrics (IJCB), 2023 (Oral) [Paper] [Extended Paper] [Code]
	Multimodal Neural Radiance Field Haidong Zhu, Yuyin Sun, Chi Liu, Lu Xia, Jiajia Luo, Nan Qiao, Ram Nevatia, and Cheng-Hao Kuo In IEEE International Conference on Robotics and Automation (ICRA), pp. 9393-9399, 2023 [Paper]
	Gait Recognition Using 3-D Human Body Shape Inference Haidong Zhu, Zhaoheng Zheng, and Ram Nevatia In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 909-918, 2023 [Paper] [Supp]
	Self-supervised Learning for Sentiment Analysis via Image-text Matching Haidong Zhu, Zhaoheng Zheng, Mohammad Soleymani, and Ram Nevatia In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1710-1714, 2022 [Paper]
	Utilizing Every Image Object for Semi-supervised Phrase Grounding Haidong Zhu, Arka Sadhu, Zhaoheng Zheng, and Ram Nevatia In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 2210-2219, 2021 [Paper]
	Curriculum DeepSDF Yueqi Duan, Haidong Zhu, He Wang, Li Yi, Ram Nevatia, and Leonidas J. Guibas In European Conference on Computer Vision (ECCV), pp. 51-67, 2020 [Paper] [Code]
	Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation Haidong Zhu, Jialin Shi, and Ji Wu In Proceedings of the International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), LNCS 11769, pp. 576-584, 2019. [Paper]
	Biologically-Constrained Graphs for Global Connectomics Reconstruction Brian Matejek, Daniel Haehn, Haidong Zhu, Donglai Wei, Toufiq Parag, and Hanspeter Pfister In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2089-2098, 2019. [Paper] [Supp] [Code]

Workshop, Survey and System Manuscrips

	AG-ReID 2023: Aerial-Ground Person Re-identification Challenge Results Kien Nguyen, Clinton Fookes, Sridha Sridharan, Feng Liu, Xiaoming Liu, Arun Ross, Dana Michalski, Huy Nguyen, Debayan Deb, Mahak Kothari, Manisha Saini, Dawei Du, Scott McCloskey, Gabriel Bertocco, Fernanda Andaló, Terrance E Boult, Anderson Rocha, Haidong Zhu, Zhaoheng Zheng, Ram Nevatia, Zaigham Randhawa, Sinan Sabri, Gianfranco Doretto In Proceedings of IEEE International Joint Conference on Biometrics (IJCB), 2023 [Paper]
	CAT-NeRF: Constancy-Aware Tx²Former for Dynamic Body Modeling Haidong Zhu, Zhaoheng Zheng, Wanrong Zheng, and Ram Nevatia In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 6618-6627, 2023 [Paper] [Code] [Example Videos]
	GAIA at SM-KBP 2020 - A Dockerized Multi-media Multi-lingual Knowledge Extraction, Clustering, Temporal Tracking and Hypothesis Generation System Manling Li, Ying Lin, Tuan Manh Lai, Xiaoman Pan, Haoyang Wen, Sha Li, Zhenhailong Wang, Pengfei Yu, Lifu Huang, Di Lu, Qingyun Wang, Haoran Zhang, Qi Zeng, Chi Han, Zixuan Zhang, Yujia Qin, Xiaodan Hu, Nikolaus Parulian, Daniel Campos, Heng Ji, Brian Chen, Xudong Lin, Alireza Zareian, Amith Ananthram, Emily Allaway, Shih-Fu Chang, Kathleen McKeown, Yixiang Yao, Michael Spector, Mitchell DeHaven, Daniel Napierski, Marjorie Freedman, Pedro Szekely, Haidong Zhu, Ram Nevatia, Yang Bai, Yifan Wang, Ali Sadeghian, Haodi Ma, Daisy Zhe Wang In Proceedings of the Thirteenth Text Analysis Conference (TAC), 2020 [Paper]
	CPARR: Category-based Proposal Analysis for Referring Relationships Chuanzi He, Haidong Zhu, Jiyang Gao, Kan Chen, and Ram Nevatia In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 4074-4083, 2020. [Paper]

Thesis

Deep Learning Based Target Delineation System

• Bachelor of Engineering, Tsinghua University, 2019.
• Advisor: Prof Ji Wu

[Thesis] [Proposal] [Midterm] [Defense]

Selected Projects

	Structural Relational Reasoning for Point Clouds • Introduced structural relational network (SRN) for reasoning. • Improved the results on public point cloud datasets. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 949-958, 2019. [Paper]
	Online Big Data Face Recognition System • Real time face recognition with data from Internet. • Big data management policy for renewing database. • Predicting relationship between the people in the image. [Code]
	Visual-audio Similarity Evaluation System • Evaluating similarity between given audio and visual fragments. • Sequence feature extraction and similarity evaluation. [Code]
	Competition & Lecture Management System • Lecture management system with wechat and website version. • Organizing information according to user's habit and need. [Code]

Website source from Jon Barron and Xingyuan Sun.