Ph.D. Student

  University of Toronto

  Email: ziyiwu [at] cs.toronto.edu

I am a fourth-year PhD student in Toronto Intelligent Systems Lab (TISL) at the University of Toronto and affiliated with the Vector Institute. My advisor is Prof. Igor Gilitschenski. I also interned at Snap working with Dr. Aliaksandr Siarohin. I was a Student Researcher at Google DeepMind with Dr. Thomas Kipf in Spring 2024.

Prior to my Ph.D., I received my Bachelor's degree from the Department of Automation, Tsinghua University, where I worked with Prof. Jiwen Lu. I spent an unforgettable summer in 2020 doing internship at Stanford University, advised by Prof. Leonidas J. Guibas.

I am broadly interested in designing machine learning systems that can perceive the world as we humans do, which I believe is the cornerstone of achieving AGI. I have been working on object-centric learning (structured representation), event-based vision (silicon retina), and generative AI (world models).

Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models
Ziyi Wu, Yulia Rubanova, Rishabh Kabra, Drew A. Hudson, Igor Gilitschenski,
Yusuf Aytar, Sjoerd van Steenkiste, Kelsey Allen, Thomas Kipf
NeurIPS 2024.
Spotlight Presentation
[Project Page]

SPAD: Spatially Aware Multiview Diffusers
Yash Kant, Ziyi Wu, Michael Vasilkovsky, Guocheng Qian, Jian Ren, Riza Alp Guler,
Bernard Ghanem, Sergey Tulyakov*, Igor Gilitschenski*, Aliaksandr Siarohin*
CVPR 2024.
[Project Page (with paper, code, and slides)]

LEOD: Label-Efficient Object Detection for Event Cameras
Ziyi Wu, Mathias Gehrig, Qing Lyu, Xudong Liu, Igor Gilitschenski
CVPR 2024.
[Paper]  [Code]  [Slides]

SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models
Ziyi Wu, Jingyu Hu*, Wuyue Lu*, Igor Gilitschenski, Animesh Garg
NeurIPS 2023 | ICLR@NeSy-GeMs workshop, 2023.
Spotlight Presentation
[Project Page (with paper and code)]  [Slides]

SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models
Ziyi Wu, Nikita Dvornik, Klaus Greff, Thomas Kipf*, Animesh Garg*
ICLR 2023 | UAI@CRL workshop, 2022 | ECCV@MVCS Challenge, 2022.
[Project Page (with paper and code)]  [Slides]

Breaking Bad: A Dataset for Geometric Fracture and Reassembly
Silvia Sellán*, Yun-Chun Chen*, Ziyi Wu*, Animesh Garg, Alec Jacobson
NeurIPS 2022 Datasets and Benchmarks Track.
Featured Paper Presentation
[Project Page (with paper, code, and data)]  [Slides]

Instance Similarity Learning for Unsupervised Feature Representation
Ziwei Wang, Yunsong Wang, Ziyi Wu, Jiwen Lu, Jie Zhou
ICCV 2021.
[Paper]  [Code]

Learning Efficient Binarized Object Detectors with Information Compression
Ziwei Wang, Jiwen Lu, Ziyi Wu, Jie Zhou
T-PAMI 2021.
[Paper]

BiDet: An Efficient Binarized Object Detector
Ziwei Wang, Ziyi Wu, Jiwen Lu, Jie Zhou
CVPR 2020.
[Paper]  [Code]  [Slides]

Journal reviewer: T-PAMI; TMLR; ISRR; RA-L;
Conference reviewer: CVPR'22-24; ICCV'23; ECCV'22-24; NeurIPS'22-24; ICML'23-24; ICLR'24-25; AAAI'23-24; IJCAI'24; IROS'22; ICRA'23-24;
Workshop reviewer: OSC@ICLR'22;

Teaching Assistant, CSC 478: Robotics Perception23 Winter
Teaching Assistant, CSC 108: Introduction to Computer Programming21 Fall, 22 Winter, 22 Fall, 23 Summer

I like basketball and soccer. My favorite players are LeBron James (well, associate G.O.A.T.?) and Lionel Messi (real G.O.A.T.!).

I love reading (especially when I am stuck in research). My favorite books are One Hundred Years of Solitude, 1984, The Plague, and Dream of the Red Chamber (红楼梦). My favorite writers are García Márquez and Albert Camus. Some of my recent (since 2017) favorites are Hannah Arendt, Hermann Hesse, Milan Kundera, Mo Yan (莫言), Tocqueville, Yukio Mishima, Yasunari Kawabata, Proust, etc. My main interests are ethics, human nature and values.

I am also an Anime fan and a lover of Visual Novel, and JRPG (added, 2023.1). Some of my favorite works are Fate/Stay Night, EVA, Perfect Blue, Hyouka, Subarashiki Hibi (a.k.a. Wonderful Everyday), and Persona 5 (added, 2023.1).

Two persons I admire the most: Kaiming He for his outstanding research tastes ("All great truths are simple in final analysis") and Elon Musk for his aspiration and enthusiasm (now in doubt, 2022.12. "Power tends to corrupt and absolute power corrupts absolutely").

I write an article (in Chinese) summarizing the experience during my CS PhD application process. Take a look here!