Hanzhe Hu

Hanzhe Hu

Google Scholar / GitHub / Email / Twitter / LinkedIn / CV

hanzheh [at] cs.cmu.edu, huhz [at] pku.edu.cn

I am a final-year Ph.D. candidate at the School of Computer Science at Carnegie Mellon University, advised by Prof. Shubham Tulsiani. I am part of the CMU Computer Vision Group. I obtained my Master's degree in Computer Science from the School of EECS at Peking University, where I was advised by Prof. Liwei Wang. I have also had the pleasure of working with Dr. Han Hu at Microsoft Research Asia (MSRA) and Prof. Xiaolong Wang at UCSD.

My research interests lie in computer vision and machine learning. Currently, I am working on video world models, unified models and reasoning-based visual generation.

I am looking for full-time research positions in industry. If you are interested, please feel free to contact me.

I am always open to research collaborations. Feel free to reach out.

News

(02/2025) One paper is accepted by CVPR2025!
(02/2024) One paper is accepted by CVPR2024!
(08/2022) I started my PhD at CMU SCS.
(07/2022) One paper is accepted by ECCV2022!
(06/2022) I graduated from Peking University!
(09/2021) One paper is accepted by NeurIPS2021 as Spotlight!
(07/2021) One paper is accepted by ICCV2021!
(07/2021) I am selected as "Top 10 Outstanding Researcher" (学术十杰), EECS of Peking University!
(03/2021) One paper is accepted by CVPR2021!
(12/2020) One paper is accepted by AAAI2021!
(07/2020) One paper is accepted by ECCV2020!
(06/2020) One paper is accepted by ICPR2020.
(03/2020) One paper is accepted by CVPR2020!
(09/2019) I began my graudate study in CS at PKU.

Publications (Full list can be found here.)

		Turbo3D: Ultra-fast Text-to-3D Generation Hanzhe Hu, Tianwei Yin, Fujun Luan, Yiwei Hu, Hao Tan, Zexiang Xu, Sai Bi, Shubham Tulsiani, Kai Zhang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025 [Paper] [Project] [Code]
		MVD-Fusion: Single-view 3D via Depth-consistent Multi-view Generation Hanzhe Hu, Zhizhuo Zhou, Varun Jampani, Shubham Tulsiani IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 [Paper] [Project] [Code]
		Learning Implicit Feature Alignment Function for Semantic Segmentation Hanzhe Hu, Yinbo Chen, Jiarui Xu, Shubhankar Borse, Hong Cai, Fatih Porikli, Xiaolong Wang European Conference on Computer Vision (ECCV), 2022 [Paper] [Code]
		Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning Hanzhe Hu, Fangyun Wei, Han Hu, Qiwei Ye, Jinshi Cui, Liwei Wang Neural Information Processing Systems (NeurIPS), 2021 (Spotlight) [Paper] [Code]
		Region-aware Contrastive Learning for Semantic Segmentation Hanzhe Hu, Jinshi Cui, Liwei Wang International Conference in Computer Vision (ICCV), 2021 [Paper] [Code]
		Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection Hanzhe Hu, Shuai Bai, Aoxue Li, Jinshi Cui, Liwei Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 [Paper] [Code]
		Context-aware Graph Convolution Network for Target Re-identification Deyi Ji, Haoran Wang, Hanzhe Hu, Weihao Gan, Wei Wu, Junjie Yan AAAI Conference on Aritifical Intelligence (AAAI), 2021 [Paper]
		Class-wise Dynamic Graph Convolution for Semantic Segmentation Hanzhe Hu, Deyi Ji, Weihao Gan, Shuai Bai, Wei Wu, Junjie Yan European Conference on Computer Vision (ECCV), 2020 [Paper]
		Boundary-aware Graph Convolution for Semantic Segmentation Hanzhe Hu, Jinshi Cui, Hongbin Zha International Conference on Pattern Recognition (ICPR), 2020 [Paper]
		Adaptive Dilated Network with Self-Correction Supervision for Counting Shuai Bai, Zhiqun He, Yu Qiao, Hanzhe Hu, Wei Wu, Junjie Yan IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 [Paper]

Academic Services

Conference Reviewer
- CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, ACM Siggraph, ACM Siggraph Asia, AISTATS, 3DV, BMVC, WACV
Journal Reviewer
- TPAMI, TIP, IJCV, TNNLS, TCSVT, Neurocomputing
Seminar Organizer
- CMU Computer Vision Reading Group

Experience

▪	May 2026 – Now	Meta Superintelligence Labs, New York, NY Research Scientist Intern
▪	May 2024 – Jan 2025	Adobe Research, San Jose, CA Research Scientist Intern
▪	Mar 2021 – Jun 2021	Microsoft Research, Beijing, China Research Intern

Teaching

16-824: Visual Learning and Recognition. TA, Spring 2025
16-825: Learning for 3D Vision. TA, Fall 2025

Honors and Awards

Award for Academic Innovation, Peking University, 2021
Merit Student of Peking University, 2021
Top 10 Outstanding Researcher (学术十杰), EECS, Peking University, 2021
Scholarship for Outstanding Research, 2020
Peking University Scholarship, 2019
Xingquan Scholarship, Nanjing University, 2018
Scholarship for Outstanding Student, Nanjing University, 2018

Thesis

Label-Efficient Learning for Object Recognition
Hanzhe Hu
Master's Thesis, Peking University, 2022