Xu Han
Make it count.
Biography
Background
I am a final-year graduate student in computer science at Huazhong University of Science and Technology, advised by Prof. Xianzhi Li. I was a research intern at King Abdullah University of Science and Technology (KAUST), working with Prof. Peter Wonka. Before that, I received my B.Eng. degree with honors from the School of Computer Science at Shandong University in 2023, where I worked closely with Prof. Mengbai Xiao.
Research interests
My research lies at the intersection of generative modeling, 3D vision, and multimodal learning. I study how models can learn useful structure from visual and spatial data, and use it to understand and generate complex scenes.
I’m always open to thoughtful collaborations across these areas.
Research outlook
I am particularly interested in world models that capture not only what an environment looks like, but also how it changes and responds to action. I hope to develop models that draw on visual, geometric, and linguistic evidence to predict future states and support reasoning and action in dynamic environments.
Publications
My work spans generative modeling, 3D vision, and multimodal learning.
* equal contribution · † corresponding author
PointDreamer: Zero-Shot 3D Textured Mesh Reconstruction From Colored Point Cloud
MoST: Efficient Monarch Sparse Tuning for 3D Representation Learning
Fancy123: One Image to High-Quality 3D Mesh Generation via Plug-and-Play Deformation
SASep: Saliency-Aware Structured Separation of Geometry and Feature for Open Set Learning on Point Clouds
More Text, Less Point: Towards 3D Data-Efficient Point-Language Understanding
Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model
MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors
patchDPCC: A Patchwise Deep Compression Framework for Dynamic Point Clouds
Academic Service
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Computer Vision (CV): MM, CVPR
Machine Learning (ML): AAAI