Zhizhong Han


Zhizhong Han is an Assistant Professor in Computer Science. Before joining Wayne State University, he had been a postdoctoral researcher with the Department of Computer Science at the University of Maryland, College Park for three years, with particular research interests in 3D computer vision, digital geometry processing and artificial intelligence. His works have been published at top-tier conferences and journals, which focus on understanding the 3D world with different shape representations, such as 3D point clouds, meshes and voxel grids, in different topics, such as 3D shape recognition, segmentation and reconstruction. He obtained his bachelor’s (2009), master’s (2012) and Ph.D. (2017) from Northwestern Polytechnical University in Pattern Recognition and Intelligent Systems.  


B.E., 2009, Northwestern Polytechnical University
M.E., 2012, Northwestern Polytechnical University
Ph.D., 2017, Northwestern Polytechnical University

Courses Taught

 CSC 4992: Introduction to Deep Learning 

 CSC 6991: Deep Learning for 3D Shapes and Scenes

Research Interests

  •  3D Computer Vision
  •  Digital Geometry Processing
  •  Artificial Intelligence
  •  3D Deep Learning

Publications (Please see my more recent publication here)

  1. Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker, DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images, International Conference on Machine Learning (ICML), 2020.
  2. Zhizhong Han, Guanhui Qiao, Yu-Shen Liu, Matthias Zwicker, SeqXY2SeqZ: Structure Learning for 3D Shapes by Sequentially Predicting 1D Occupancy Segments From 2D Coordinates, European Conference on Computer Vision (ECCV), 2020.
  3. Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker, ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences, ACM Multimedia conference (ACMMM), 2020.
  4. Yue Jiang, Dantong Ji, Zhizhong Han, Matthias Zwicker, SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
  5. Wen Xin, Tianyang Li, Zhizhong Han, Yu-Shen Liu, Point Cloud Completion by Skip-attention Network with Hierarchical Folding, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
  6. Tao Hu, Zhizhong Han, Matthias Zwicker, 3D Shape Completion with Multi-view Consistent Inference, AAAI Conference on Artificial Intelligence (AAAI), 2020.
  7. Han Liu, Zhizhong Han, Yu-Shen Liu, Ming Gu, Fast Low-rank Metric Learning for Large-scale and High-dimensional Data, Conference on Neural Information Processing Systems (NeurIPS), 2019.
  8. Zhizhong Han, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker, Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds From Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction, International Conference on Computer Vision (ICCV), 2019.
  9. Zhizhong Han, Xinhai Liu, Yu-Shen Liu, Matthias Zwicker, Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views, International Joint Conference on Artificial Intelligence (IJCAI), 2019.
  10. Zhizhong Han, Mingyang Shang, Yu-Shen Liu, Matthias Zwicker, View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions, AAAI Conference on Artificial Intelligence (AAAI), 2019.


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