Yunzhi Zhang

I am a Ph.D. student in the Computer Science Department at Stanford University, advised by Jiajun Wu. I am affiliated with the Stanford Artificial Intelligence Laboratory and the Stanford Vision and Learning Lab.

Previously, I received B.A. in computer science and pure mathematics from UC Berkeley. I am grateful to receive advice from Pieter Abbeel and Lerrel Pinto when I did research as part of the Berkeley Artificial Intelligence Lab.

Email: yzzhang at cs dot stanford dot edu / Google Scholar / Github / Twitter

Research

The Scene Language: Representing Scenes with Programs, Words, and Embeddings

Yunzhi Zhang, Zizhang Li, Matt Zhou, Shangzhe Wu, Jiajun Wu

[arXiv] [Webpage] [Code]

arXiv Preprint 2024

Birth and Death of a Rose

Chen Geng, Yunzhi Zhang, Shangzhe Wu, Jiajun Wu

[arXiv] [Webpage]

arXiv Preprint 2024

Diffusion Self-Distillation for Zero-Shot Customized Image Generation

Shengqu Cai, Eric Ryan Chan, Yunzhi Zhang, Leonidas Guibas, Jiajun Wu, Gordon Wetzstein

[arXiv] [Webpage]

arXiv Preprint 2024

3D Congealing: 3D-Aware Image Alignment in the Wild

Yunzhi Zhang, Zizhang Li, Amit Raj, Andreas Engelhardt, Yuanzhen Li, Tingbo Hou, Jiajun Wu, Varun Jampani

[arXiv] [Webpage]

ECCV 2024

Ponymation: Learning 3D Animal Motions from Unlabeled Online Videos

Keqiang Sun*, Dor Litvak*, Yunzhi Zhang, Hongsheng Li, Jiajun Wu†, Shangzhe Wu† (*equal contribution, †equal advising)

[arXiv] [Webpage] [Code]

ECCV 2024

Learning the 3D Fauna of the Web

Zizhang Li*, Dor Litvak*, Ruining Li, Yunzhi Zhang, Tomas Jakab, Christian Rupprecht, Shangzhe Wu†, Andrea Vedaldi†, Jiajun Wu† (*equal contribution, †equal advising)

[arXiv] [Webpage] [Demo] [Code]

CVPR 2024

ZeroNVS: Zero-Shot 360-Degree View Synthesis from a Single Real Image

Kyle Sargent, Zizhang Li, Tanmay Shah, Charles Herrmann, Hong-Xing Yu, Yunzhi Zhang, Eric Ryan Chan, Dmitry Lagun, Li Fei-Fei, Deqing Sun, Jiajun Wu

[arXiv] [Webpage] [Code]

CVPR 2024

Language-Informed Visual Concept Learning

Sharon Lee*, Yunzhi Zhang*, Shangzhe Wu, Jiajun Wu (*equal contribution, alphabetical order)

[arXiv] [Webpage]

ICLR 2024

Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark

Zhengfei Kuang*, Yunzhi Zhang*, Hong-Xing Yu, Samir Agarwala, Shangzhe Wu, Jiajun Wu (*equal contribution)

[arXiv] [Webpage] [Code]

NeurIPS 2023 Datasets and Benchmarks Track

Holistic Evaluation of Text-to-Image Models

Tony Lee*, Michihiro Yasunaga*, Chenlin Meng*, ... (18 authors) (*equal contribution)

[arXiv] [Webpage] [Code]

NeurIPS 2023 Datasets and Benchmarks Track

Seeing a Rose in Five Thousand Ways

Yunzhi Zhang, Shangzhe Wu, Noah Snavely, Jiajun Wu

[arXiv] [Webpage] [Code]

CVPR 2023

MaskViT: Masked Visual Pre-Training for Video Prediction

Agrim Gupta, Stephen Tian, Yunzhi Zhang, Jiajun Wu, Roberto Martín-Martín, Li Fei-Fei

[arXiv] [Webpage]

ICLR 2023

IKEA-Manual: Seeing Shape Assembly Step by Step

Ruocheng Wang, Yunzhi Zhang, Jiayuan Mao, Ran Zhang, Chin-Yi Cheng, Jiajun Wu

[Paper] [Webpage]

NeurIPS 2022 Datasets and Benchmarks Track

Video Extrapolation in Space and Time

Yunzhi Zhang, Jiajun Wu

[arXiv] [Webpage]

ECCV 2022

Translating a Visual LEGO Manual to a Machine-Executable Plan

Ruocheng Wang, Yunzhi Zhang, Jiayuan Mao, Chin-Yi Cheng, Jiajun Wu

[arXiv] [Webpage] [Code]

ECCV 2022

VideoGPT: Video Generation using VQ-VAE and Transformers

Wilson Yan*, Yunzhi Zhang*, Pieter Abbeel, Aravind Srinivas (*equal contribution)

[arXiv] [Webpage] [Code]

arXiv Preprint 2021

Automatic Curriculum Learning through Value Disagreement

Yunzhi Zhang, Pieter Abbeel, Lerrel Pinto

[arXiv] [Webpage] [Code]

NeurIPS 2020

Asynchronous Methods for Model-Based Reinforcement Learning

Yunzhi Zhang*, Ignasi Clavera*, Boren Tsai, Pieter Abbeel (*equal contribution)

[arXiv] [Webpage] [Code]

CoRL 2019 (Spotlight)

Teaching

Teaching Assistant, Stanford Psych225/CS322: Triangulating Intelligence: Melding Neuroscience, Psychology, and AI, Winter 2022
Teaching Assistant, UC Berkeley CS170: Efficient Algorithms and Intractable Problems, Fall 2019
Teaching Assistant, UC Berkeley CS70: Discrete Mathematics and Probability Theory, Spring 2018

Honors and Awards

Stanford Interdisciplinary Graduate Fellowship, 2023
Honorable Mentions, CRA Outstanding Undergraduate Researchers, 2020
Arthur M. Hopkin Award, 2018-2019

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