⬆️ Try to drag around!! ⬆️

Me in 3D, There is no way to keep smiling while being scanned...

➡️ If you want to get to know me more in 2D... ⬅️

About me

I am Zhaoning Wang, currently a PhD student at University of Michigan, advised by Prof. Jun Gao. Previously, I was fortunate to intern at Hillbot Inc. and Sulab, where I was mentored by Dr. Minghua Liu. I also had amazing experience working with Prof. Chen Chen, Fernando De la Torre and Sharon Li.


I am interested in using state-of-the-art deep learning and computer vision to improve machine perceptions and let them aware of their surroundings.

I am particularly interested in Perception and Understanding, Embodied AI, and World Models. I am also keen on Data-Driven Computer Vision and Computer Graphics. I believe these areas will fundamentally help bridge the gap between the virtual and physical worlds—that is, between Computers and Reality—and enable the next generation of Embodied AI systems.

I’m always open to research collaborations in this area. Feel free to drop me an email at :

zhaoning [dot] eric [dot] wang [at] gmail [dot] com.

Publications

AFUN: Towards an Affordance Foundation Model for Functionality Understanding
arXiv preprint, 2026

PartUV: Part-Based UV Unwrapping of 3D Meshes
ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia (SIGGRAPH Asia), 2025

MeshFormer: High-Quality Mesh Generation with 3D-Guided Reconstruction Model
Conference on Neural Information Processing Systems (NeurIPS) [Oral], 2024

LucidDreaming: Controllable Object-Centric 3D Generation
European Conference on Computer Vision (ECCV) Workshop, 2024

ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback.
European Conference on Computer Vision (ECCV), 2024

ZOOM: Zero-shot Model Diagnosis
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023

VOS: Learning What You Don’t Know by Virtual Outliers Synthesis.
International Conference on Learning Representations (ICLR), 2022