Zehuan Huang (黄泽桓)  Final Year Master Student @ Beihang University Email: huangzehuan@buaa.edu.cn [Github] [Google Scholar] [Twitter] [CV]

Biography

I am a master student in School of Software from Beihang University now, supervised by Prof. Lu Sheng.

My prior research focused on applying deep generative models to 3D asset creation, encompassing the generation of 3D objects, scenes, textures, and animations. My current research interests lie in world models and simulation, including

  (i) Generalizable 3D Foundation Models: Generative 3D Reconstruction, Physics Modeling
  (ii) Multi-Modal Generative Models: Multi-Modal Foundation Models, Unified Understanding and Generation
  (iii) World Models: Real-Time, Long-term Memory, Interactive, Physics-Compliance

I am grateful to all my collaborators and mentors along the way. I first started doing research under the guidance of Prof. Miao Wang. Then I started working on deep learning related projects under the supervision of Prof. Lu Sheng. Besides, I also successively haved intern at MiniMax, Shanghai AI Lab, and VAST, and I'm fortunate to have worked closely with Junting Dong, Yuan-Chen Guo and Yanpei Cao.

I am always open to academic and industrial collaborations, if you share the vision, please do not hesitate to contact me!

News

Selected Publications

	AnimaX: Animating the Inanimate in 3D with Joint Video-Pose Diffusion Models Zehuan Huang, Haoran Feng, Yangtian Sun, Yuanchen Guo, Yanpei Cao, Lu Sheng SIGGRAPH Asia 2025 [Project Page] / [Paper] / [机器之心] TL;DR: Animate any 3D skeleton with joint video-pose diffusion models.
	MV-Adapter: Multi-view Consistent Image Generation Made Easy Zehuan Huang, Yuan-Chen Guo, Haoran Wang, Ran Yi, Lizhuang Ma, Yan-Pei Cao✉, Lu Sheng✉ ICCV 2025 [Project Page] / [Paper] / [Code] / [机器之心] TL;DR: Versatile multi-view generation with various base models and conditions, and high-quality 3D texture generation.
	MIDI: Multi-Instance Diffusion for Single Image to 3D Scene Generation Zehuan Huang, Yuan-Chen Guo, Xingqiao An, Yunhan Yang, Yangguang Li, Zi-Xin Zou, Ding Liang, Xihui Liu, Yan-Pei Cao✉, Lu Sheng✉ CVPR 2025 [Project Page] / [Paper] / [Code] / [机器之心] TL;DR: MIDI-3D extends image-to-3D object generation models to multi-instance diffusion models for compositional 3D scene generation.
	Ouroboros3D: Image-to-3D Generation via 3D-aware Recursive Diffusion Hao Wen*, Zehuan Huang*, Yaohui Wang, Xinyuan Chen, Yu Qiao, Lu Sheng CVPR 2025 [Project Page] TL;DR: Transfer the two-stage image-to-3D pipeline into a unified recursive diffusion process, thereby reducing the data bias of each stage and improving the quality of generated 3D.
	TELA: Text to Layer-wise 3D Clothed Human Generation Junting Dong, Qi Fang, Zehuan Huang, Xudong Xu, Jingbo Wang, Sida Peng, Bo Dai✉ ECCV 2024 [Project Page]
	EpiDiff: Enhancing Multi-View Synthesis via Localized Epipolar-Constrained Diffusion Zehuan Huang*, Hao Wen*, Junting Dong*, Yaohui Wang, Yangguang Li, Xinyuan Chen, Yan-Pei Cao, Ding Liang, Yu Qiao, Bo Dai✉, Lu Sheng✉ CVPR 2024 [Project Page]

* Equal contribution. † Project Lead. ✉ Corresponding author.

Leading Projects

VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space Lin Li*, Zehuan Huang*†, Haoran Feng, Gengxiong Zhuang, Rui Chen, Chunchao Guo, Lu Sheng✉ Under Review [Paper] / [Code] TL;DR: A training-free 3D editing approach that performs precise and coherent editing in native 3D latent space instead of multi-view space.

	Multi-Agent Amodal Completion: Direct Synthesis with Fine-Grained Semantic Guidance Hongxing Fan, Lipeng Wang, Haohua Chen, Zehuan Huang†, Lu Sheng✉ ACM MM 2025 Oral [Paper] / [Code] TL;DR: A multi-agent framework for high-fidelity amodal completion.
	Personalize Anything for Free with Diffusion Transformer Haoran Feng*, Zehuan Huang*†, Lin Li, Hairong Lv, Lu Sheng✉ Under Review [Project Page] / [Paper] / [Code] TL;DR: Customize any subject with advanced DiT without additional fine-tuning.
	Parts2Whole: Generalizable Multi-Part Portrait Customization Hongxing Fan*, Zehuan Huang*†, Lipeng Wang, Haohua Chen, Li Yin, Lu Sheng✉ TIP 2025 [Project Page] / [Paper] / [Code] TL;DR: A unified framework for customizing human images from user-specified part images.

Open-Source Projects

Honors & Awards

Educations

Industrial Experience

Services

Reviewer

ICLR, NeurIPS, CVPR, ICCV, ACM MM, AAAI, TCSVT

In-School

2023 Fall ~ 2025 Spring, part-time technology counselor in School of Software, Beihang University
2024 Spring, TA in Image Processing and Computer Vision, instructed by Prof. Lu Sheng