About Me

I obtained my Ph.D. degree in Computer Science at City University of Hong Kong, supervised by Prof. Junhui Hou. I was also fortunate to work closely with Prof. Ying He from NTU and Prof. Wenping Wang from TAMU. Previously, I worked as a research intern guided by Prof. Runmin Cong. I received my B.Sc. degree in Electronic Information Science and Technology at Beijing Normal University.

News

• [2023.09] Two papers, NeuroGF for neural geodesics learning, UPIDet for cross-modal 3D object detection, got accepted by NeurIPS-2023.
• [2023.12] One paper, Cross-PCC for cross-modal image-assisted unsupervised 3D point cloud completion, got accepted by TMM.
• [2023.12] One paper, PointVST for self-supervised 3D point cloud backbone pre-training, got accepted by TVCG.
• [2024.06] One paper, SPCV for spatio-temporal structurization of dynamic 3D point cloud sequences, got accepted by TPAMI.
• [2024.09] One paper, Flatten Anything Model (FAM) for neural surface parameterization (UV unwrapping), got accepted by NeurIPS-2024.
• [2025.03] One paper, Human as Points (HaP) for single-image 3D human reconstruction, got accepted by TPAMI.

Research

The latest trend in the artificial intelligence era continues to blur the boundaries of different research domains and data modalities. In general, I have broad interests in developing deep learning models to solve various geometry, vision, and graphics problems.

My research during Ph.D. mainly includes the following tasks and topics:

• Geometric (Mesh, Point Cloud, Implicit Field) Computing and Modeling;
• Neural 3D Representation, Rendering, Reconstruction, and Generation;
• Multi-Modal (2D-3D, Visual-Geometric) Learning: Pre-training, Alignment, Fusion, Distillation.

I am particularly interested in Neuralized Geometry Processing, i.e., (1) (at the data level) exploring neural representations for geometric data; (2) (at the model level) replacing conventional geometric computation/optimization algorithms with more powerful neural architectures.

My current research concentrates on 3D Generative Models and AI for Games.

Services

• Conference Reviewer: NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, ACM MM, IJCAI, CVM, VCIP, etc.

• Journal Reviewer: TIP, TVCG, TCSVT, TITS, TGRS, JSTARS, IEEE/CAA Journal of Automatica Sinica, Scientific Reports, Multimedia Systems, The Visual Computer, Journal of Electronic Imaging, Virtual Reality & Intelligent Hardware, etc.

Selected Publications

	FlexPara: Flexible Neural Surface Parameterization Yuming Zhao, Qijian Zhang, Junhui Hou, Jiazhi Xia, Wenping Wang, Ying He Pre-print
	SuperCarver: Texture-Consistent 3D Geometry Super-Resolution for High-Fidelity Surface Detail Generation Qijian Zhang, Xiaozheng Jian, Xuan Zhang, Wenping Wang, Junhui Hou Pre-print
	HuGDiffusion: Generalizable Single-Image Human Rendering via 3D Gaussian Diffusion Yingzhi Tang, Qijian Zhang, Junhui Hou Pre-print

	Human as Points: Explicit Point-based 3D Human Reconstruction from Single-view RGB Images Yingzhi Tang, Qijian Zhang, Junhui Hou, Yebin Liu TPAMI 2025
	Flatten Anything: Unsupervised Neural Surface Parameterization Qijian Zhang, Junhui Hou, Wenping Wang, Ying He NeurIPS 2024
	Dynamic 3D Point Cloud Sequences as 2D Videos Yiming Zeng, Junhui Hou, Qijian Zhang, Siyu Ren, Wenping Wang TPAMI 2024
	PointVST: Self-Supervised Pre-training for 3D Point Clouds via View-Specific Point-to-Image Translation Qijian Zhang, Junhui Hou TVCG 2023
	Leveraging Single-View Images for Unsupervised 3D Point Cloud Completion Lintai Wu, Qijian Zhang, Junhui Hou, Yong Xu TMM 2023
	NeuroGF: A Neural Representation for Fast Geodesic Distance and Path Queries Qijian Zhang, Junhui Hou, Yohanes Yudhi Adikusuma, Wenping Wang, Ying He NeurIPS 2023
	Unleash the Potential of Image Branch for Cross-modal 3D Object Detection Yifan Zhang, Qijian Zhang, Junhui Hou, Yixuan Yuan, Guoliang Xing NeurIPS 2023
	PointMCD: Boosting Deep Point Cloud Encoders via Multi-view Cross-modal Distillation for 3D Shape Recognition Qijian Zhang, Junhui Hou, Yue Qian TMM 2023
	GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation Yifan Zhang, Qijian Zhang, Zhiyu Zhu, Junhui Hou, Yixuan Yuan IJCV 2023
	Task-Oriented Compact Representation of 3D Point Clouds via A Matrix Optimization-Driven Network Yue Qian, Junhui Hou, Qijian Zhang, Yiming Zeng, Sam Kwong, Ying He TCSVT 2023
	Flattening-Net: Deep Regular 2D Representation for 3D Point Cloud Analysis Qijian Zhang, Junhui Hou, Yue Qian, Yiming Zeng, Juyong Zhang, Ying He TPAMI 2023
	RegGeoNet: Learning Regular Representations for Large-Scale 3D Point Clouds Qijian Zhang, Junhui Hou, Yue Qian, Antoni B. Chan, Juyong Zhang, Ying He IJCV 2022
	WarpingGAN: Warping Multiple Uniform Priors for Adversarial 3D Point Cloud Generation Yingzhi Tang, Yue Qian, Qijian Zhang, Yiming Zeng, Junhui Hou, Xuefei Zhe CVPR 2022
	IDEA-Net: Dynamic 3D Point Cloud Interpolation via Deep Embedding Alignment Yiming Zeng, Yue Qian, Qijian Zhang, Junhui Hou, Yixuan Yuan, Ying He CVPR 2022
	Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images Qijian Zhang, Runmin Cong, Chongyi Li, Ming-Ming Cheng, Yuming Fang, Xiaochun Cao, Yao Zhao, Sam Kwong TIP 2021
	CoADNet: Collaborative Aggregation-and-Distribution Networks for Co-Salient Object Detection Qijian Zhang*, Runmin Cong* , Junhui Hou, Chongyi Li, Yao Zhao NeurIPS 2020