Research
I am broadly interested in Computer Vision, Machine Learning and Robotics, with a focus on 3D Vision and Multi-modal Learning.
I currently work on 3D affordance. Previously, I have also worked on the following fields: (i) 3D visual grounding, (ii) 3D visual question answering, (iii) point cloud completion, (iv) pedestrian trajectory prediction.
My research goal is to develop computer vision techniques for real-world embodied agents and autonomous systems, enhancing their capability to perceive and reason effectively in uncertain environments.
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Multi-Object 3D Grounding with Dynamic Modules and Language Informed Spatial Attention
Haomeng Zhang, Chiao-An Yang, Raymond A. Yeh
NeurIPS 2024
Coming Soon!
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Hyperspherical Embedding for Point Cloud Completion
Junming Zhang, Haomeng Zhang, Ram Vasudevan, Matthew Johnson-Roberson
CVPR 2023
arXiv /
Project Page /
Code
We propose a hyperspherical module which could be inserted into any existing Encoder-Decoder structure and consistently improve the point cloud completion result in both single-task and multi-task learning.
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Teaching
Teaching Assistant of CS 47100 Introduction to Artificial Intelligence, Purdue, Fall 2023, Spring 2024, Fall 2024.
Teaching Assistant of CS 444 Deep Learning for Computer Vision, UIUC, Spring 2023.
Teaching Assistant of CS 441 Applied Machine Learning, UIUC, Fall 2022, Spring 2022, Fall 2021.
Teaching Assistant of VP 140 Physics I, SJTU, Summer 2019.
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Service
Conference Reviewer: NeurIPS, ICLR.
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Awards & Honors
Outstanding Graduate, Shanghai Municipal Education Commission, 2021.
James B. Angell Scholar, University of Michigan, 2021.
National Scholarship (Top 1%), Ministry of Education of China, 2019.
Undergraduate Excellent Scholarship (Top 10%), Shanghai Jiao Tong University, 2018, 2019.
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Updated at Sept. 2024. Thanks Jon Barron for this amazing template.
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