Zeyu Zhang

Zeyu Zhang is an undergraduate researcher under the guidance of Prof. Richard Hartley and Prof. Ian Reid. His research interests are rooted in computer vision, focusing on generative 3D Generation. Specifically, he is dedicated to advancing efficient and high-quality motion and avatar generation. With extensive experience across multiple research disciplines, Zeyu actively explores cutting-edge advancements in both the foundational and applied aspects of artificial intelligence. Zeyu is actively seeking PhD opportunities in 26 Fall.

News

(07/19/2024) 🎉 Our paper Motion Avatar has been accepted to BMVC 2024!
(07/02/2024) 🎉 Our paper Motion Mamba has been accepted to ECCV 2024!
(03/13/2024) 🎉 Our paper Motion Mamba has been featured in Daily Papers!

Publications

Selected publications are highlighted.

	Motion Mamba: Efficient and Long Sequence Motion Generation Zeyu Zhang^∗, Akide Liu^∗, Ian Reid, Richard Hartley, Bohan Zhuang, Hao Tang^✉ *ECCV 2024* Human motion generation is a key goal in generative computer vision, and we propose Motion Mamba, a model using state space models (SSMs) with Hierarchical Temporal Mamba (HTM) and Bidirectional Spatial Mamba (BSM) blocks, achieving up to 50% FID improvement and 4x speedup on HumanML3D and KIT-ML datasets, showcasing efficient and high-quality long sequence motion modeling.
	Motion Avatar: Generate Human and Animal Avatars with Arbitrary Motion Zeyu Zhang^∗, Yiran Wang^∗, Biao Wu^∗, Shuo Chen, Zhiyuan Zhang, Shiya Huang, Wenbo Zhang, Meng Fang, Ling Chen, Yang Zhao^✉ *BMVC 2024* Our paper introduces a novel agent-based approach called Motion Avatar for generating customizable human and animal 3D avatars with motions via text queries, coordinated by an LLM planner, and supported by the new Zoo-300K animal motion dataset.
	Sine Activated Low-Rank Matrices for Parameter Efficient Learning Yiping Ji^∗, Hemanth Saratchandran^∗, Cameron Gordon, Zeyu Zhang, Simon Lucey^✉ *ICLR 2025* We propose a novel theoretical framework integrating a sinusoidal function into low-rank decomposition, enhancing parameter efficiency and model accuracy across diverse neural network applications such as Vision Transformers, Large Language Models, Neural Radiance Fields, and 3D shape modeling.
	Hazards in Daily Life? Enabling Robots to Proactively Detect and Resolve Anomalies Zirui Song, Guangxian Ouyang, Meng Fang, Hongbin Na, Zijing Shi, Zhenhao Chen, Yujie Fu, Zeyu Zhang, Shiyu Jiang, Miao Fang, Ling Chen, Xiuying Chen^✉ *NAACL 2025 Main* Household robots struggle to detect hazards. We propose anomaly scenario generation using multi-agent brainstorming and 3D simulations, enhancing robotic skills in hazard detection, hygiene management, and child safety through diverse environments.

Research Experience

	Research Intern Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) May 2024 - June 2024 Worked on unsupervised classification of cellular structures based on cryo-electron tomography (cryo-ET), hosted by Assoc. Prof. Min Xu (CMU, MBZUAI) and Prof. Ian Reid (MBZUAI, AIML).
	Research Assistant La Trobe University Apr 2024 - Dec 2024 Worked on 3D generation and AI for Heath, hosted by Dr. Yang Zhao (La Trobe University).
	Research Assistant Monash University Feb 2024 - May 2024 Worked on 3D/4D generative learning, specifically focusing on text-guided human motion and avatar generation, hosted by Prof. Reza Haffari (Monash University), and also worked with Prof. Bohan Zhuang (ZJU, Monash University).
	Research Intern National Computational Infrastructure (NCI) Feb 2023 - Jun 2023 Worked on long tail large scale multi-label text classification, hosted by Dr. Jingbo Wang (NCI).
	Visiting Student Researcher Australian Institute for Machine Learning (AIML) Nov 2022 - Jan 2024 Worked on 3D medical imaging analysis, with a particular focus on semantic segmentations of tumors, hemorrhages, and organs at risk, advised by Prof. Ian Reid (MBZUAI, AIML), also worked with Dr. Bowen Zhang (AIML), Dr. Yutong Xie (AIML), and Dr. Qi Chen (AIML).
	Research Assistant Flinders Health and Medical Research Institute (FHMRI) Nov 2022 - Dec 2024 Worked on 3D medical imaging analysis, particularly in the realms of 2D and 3D medical reDec 2024ation learning and explainable AI, hosted by Dr. Minh-Son To (FHMRI).
	Student Researcher The Australian National University (ANU) Jul 2022 - Nov 2022 Worked on diabetes diagnosis in deep learning, advised by Dr. Md Zakir Hossain (ANU, Curtin University, CSIRO Data61), also worked with Dr. Khandaker Asif Ahmed (CSIRO), Mr. Md Rakibul Hasan (Curtin University, Brac University), and Prof. Tom Gedeon (Curtin University, ANU, Óbuda University).

Education

Bachelor of Science (Advanced) (Honours)
The Australian National University (ANU)
Jul 2021 - Jun 2025 (Expected)
Major: Computer Science, Minor: Mathematics

Visiting Student
Imperial College London
Jul 2022
Quantitative Sciences Research Institute (QSRI)

Visiting Student
University College London (UCL)
Jul 2022

Talks

(07/22/2024) Motion Mamba: Efficient and Long Sequence Motion Generation @ miHoYo, Shanghai. You can find our slides here.