Zhizhong Han - Wayne State University

News

[03/2024]	One paper on large generative models for UDFs is accepted at CVPR 2024.
[01/2024]	One paper on point cloud represenation learning is accepted at ICRA 2024.
[12/2023]	One paper on point cloud upsampling is accepted at AAAI 2024.
[09/2023]	Three papers on virtual SLAM, image to point cloud registration, and point cloud normal estimation are accepted at NeurIPS 2023.
[08/2023]	One paper on point cloud normal estimation is accepted at SIGGRAPH asia 2023.
[07/2023]	Four papers on neural implicit representations and point cloud understanding are accepted at ICCV 2023.
[06/2023]	Glad to get invited as an Area Chair at CVPR 2024.
[05/2023]	Glad to receive the Richard Barber Interdisciplinary Research Award.
[04/2023]	One paper on Learning neural implicit through mapping noise to noise is accepted for short live presentation at ICML 2023.
[03/2023]	Glad to get invited as an Area Chair at BMVC 2023.
[03/2023]	Glad to get invited as an Area Chair at NeurIPS 2023.
[02/2023]	Five papers on neural implicit representations and point cloud understanding are accepted at CVPR 2023.
[12/2022]	I gave an invited talk on Neural Implicit Representations for Surface Reconstruction at Meta Reality Labs, hosted by Dr. Yunyang Xiong.
[12/2022]	Glad to get invited as an Area Chair at ICCV 2023.
[12/2022]	Glad to get invited as a Senior PC member at IJCAI 2023.
[11/2022]	I gave an invited talk on Neural Implicit Representations for Surface Reconstruction for the Department of CSE at Michigan State University, hosted by Prof. Xiaoming Liu.
[10/2022]	Glad to get invited as an Area Chair at CVPR 2023.
[10/2022]	I gave an invited talk on Neural Implicit Representations for Surface Reconstruction for the Department of CS at City University of Hong Kong, hosted by Prof. Junhui Hou.
[09/2022]	Two papers on neural implicit representations and point normal estimation are accepted at NeurIPS 2022.
[08/2022]	Glad to get invited as an Area Chair at WACV 2023.
[07/2022]	Glad to get invited as an Area Chair at BMVC 2022.
[07/2022]	One paper on neural implicit representations is accepted at ECCV 2022.
[03/2022]	Four papers on neural implicit representations and point cloud generation are accepted at CVPR 2022.
[03/2022]	One paper on point cloud completion is accepted at TPAMI.
[07/2021]	Two papers on shape completion and unsupervised structure learning for point clouds are accepted at ICCV 2021.
[06/2021]	One paper on unsupervised feature learning for 3D shapes is accepted at ACMMM 2021.
[05/2021]	One paper on the learning of implicit function from point clouds is accepted at ICML 2021.
[03/2021]	Two papers on 3D point clouds completion are accepted at CVPR 2021.
[01/2021]	One paper on fine grained 3D shape analysis is accepted at TIP.
[08/2020]	Two papers on 3D point cloud representation learning and multi-sketch 3D shape modeling are accepted at TIP.
[08/2020]	One paper on cross modal representation learning is accepted at TCSVT.
[08/2020]	One paper on dense 3D point cloud reconstruction is accepted at WACV 2020.
[08/2020]	Two papers on 3D shape captioning and 3D point cloud segmentation are accepted at ACMMM 2020.
[07/2020]	One paper on supervised learning of 3D implicit function is accepted at ECCV 2020.
[06/2020]	One paper on unsupervised structure learning for 3D point clouds is accepted at ICML 2020.
[03/2020]	One paper on feature learning for 3D point clouds is accepted at GMP 2020.
[02/2020]	Two papers on differentiable rendering for SDF and 3D point cloud completion are accepted at CVPR 2020.
[11/2019]	Our paper on 3D shape completion is accepted at AAAI 2020.
[09/2019]	Our paper on small object arrangement in 3D scenes is accepted at TVCG.
[09/2019]	Our paper on low rank metric learning is accepted at NeurIPS 2019.
[08/2019]	Our paper on 3D point cloud understanding from multiple angles is accepted at ICCV 2019.
[07/2019]	One paper on unsupervised 3D point cloud feature learning is accepted at ACMMM 2019.
[05/2019]	Two papers on multi-view based 3D shape understanding are accepted at IJCAI 2019.
[03/2019]	One paper on GAN based 3D scene enhancement generation is accepted at CGI 2019.
[11/2018]	Three papers on unsupervised 3D feature learning, point cloud processing, and 3D-Text joint understanding are accepted at AAAI 2019.

Academic Service

Conference reviewer:
NeurIPS: 2021, 2022, 2023 (Area Chair)
ICML: 2022, 2023, 2024
ECCV: 2022
CVPR: 2022, 2023 (Area Chair), 2024 (Area Chair)
ICCV: 2023 (Area Chair)
SIGGRAPH: 2018, 2022
SIGGRAPH Asia: 2023
ICLR: 2022
AAAI: 2022 (Program Committee)
IJCAI: 2023 (Senior Program Committee), 2024 (Senior Program Committee)
WACV: 2022, 2023 (Area Chair)
3DV: 2022
BMVC: 2022 (Area Chair), 2023 (Area Chair)

Journal reviewer:
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Transactions on Graphics
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Image Processing
IEEE Transactions on Multimedia
IEEE Transactions on Cybernetics
IEEE Transactions on Systems, Man and Cybernetics: Systems
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Medical Imaging
IEEE Transactions on Industrial Informatics
IEEE Transactions on Industrial Electronics
IEEE Journal of Biomedical and Health Informatics
IEEE Access
The Visual Computer
Computer-Aided Design
Transactions on Machine Learning Research
ACM Transactions on Multimedia Computing, Communications, and Applications
ACM Transactions on Asian and Low-Resource Language Information Processing
EURASIP Journal on Image and Video

Publications

Preprint

2024

	UDiFF: Generating Conditional Unsigned Distance Fields with Optimal Wavelet Diffusion Junsheng Zhou, Weiqi Zhang, Baorui Ma, Kanle Shi, Yu-Shen Liu, Zhizhong Han (* indicates equal contribution) IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
	3D-OAE: Occlusion Auto-Encoders for Self-Supervised Learning on Point Clouds Junsheng Zhou, Xin Wen, Baorui Ma, Yu-Shen Liu, Yue Gao, Yi Fang, Zhizhong Han IEEE International Conference on Robotics and Automation (ICRA), 2024. [Paper][Code]
	Learning Continuous Implicit Field with Local Distance Indicator for Arbitrary-Scale Point Cloud Upsampling Shujuan Li, Junsheng Zhou, Baorui Ma, Yu-Shen Liu, Zhizhong Han (* indicates equal contribution) The AAAI Conference on Artificial Intelligence (AAAI), 2024. [Paper][Code][Project Page]

2023

	Learning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors Pengchong Hu, Zhizhong Han Conference on Neural Information Processing Systems (NeurIPS), 2023. [Paper][Code][Project Page]
	Differentiable Registration of Images and LiDAR Point Clouds with VoxelPoint-to-Pixel Matching Junsheng Zhou, Baorui Ma, Wenyuan Zhang, Yi Fang, Yu-Shen Liu, Zhizhong Han Conference on Neural Information Processing Systems (NeurIPS), 2023. (Spotlight) [Paper][Code]
	NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function Qing Li, Huifang Feng, Kanle Shi, Yue Gao, Yi Fang, Yu-Shen Liu, Zhizhong Han Conference on Neural Information Processing Systems (NeurIPS), 2023. [Paper][Code]
	Neural Gradient Learning and Optimization for Oriented Point Normal Estimation Qing Li, Huifang Feng, Kanle Shi, Yi Fang, Yu-Shen Liu, Zhizhong Han SIGGRAPH Asia, 2023. [Paper][Code]
	Coordinate Quantized Neural Implicit Representations for Multi-view Reconstruction Sijia Jiang, Jing Hua, Zhizhong Han International Conference on Computer Vision (ICCV), 2023. [Paper][Code][Project Page]
	GridPull: Towards Scalability in Learning Implicit Representations from 3D Point Clouds Chao Chen, Yu-Shen Liu, Zhizhong Han International Conference on Computer Vision (ICCV), 2023. [Paper][Code]
	Learning a More Continuous Zero Level Set in Unsigned Distance Fields through Level Set Projection Junsheng Zhou, Baorui Ma, Shujuan Li, Yu-Shen Liu, Zhizhong Han (* indicates equal contribution) International Conference on Computer Vision (ICCV), 2023. [Paper][Code]
	Retro-FPN: Retrospective Feature Pyramid Network for Point Cloud Semantic Segmentation Peng Xiang, Xin Wen, Yu-Shen Liu, Hui Zhang, Yi Fang, Zhizhong Han International Conference on Computer Vision (ICCV), 2023. [Paper][Code]
	Fast Learning Radiance Fields by Shooting Much Fewer Rays Wenyun Zhang, Ruofan Xing, Yunfan Zeng, Yu-Shen Liu, Kanle Shi, Zhizhong Han IEEE Transactions on Image Processing, 2023. [Paper][Code]
	Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping Baorui Ma, Yu-Shen Liu, Zhizhong Han International Conference on Machine Learning (ICML), 2023. (Oral presentation) [Paper][Code]
	Towards Better Gradient Consistency for Neural Signed Distance Functions via Level Set Alignment Baorui Ma, Junsheng Zhou, Yu-Shen Liu, Zhizhong Han (* indicates equal contribution) IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [Paper][Code]
	Unsupervised Inference of Signed Distance Functions from Single Sparse Point Clouds without Learning Priors Chao Chen, Yu-Shen Liu, Zhizhong Han IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [Paper][Code]
	LP-DIF: Learning Local Pattern-specific Deep Implicit Function for 3D Objects and Scenes Meng Wang, Yu-Shen Liu, Yue Gao, Kanle Shi, Yi Fang, Zhizhong Han IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [Paper][Code]
	SHS-Net: Learning Signed Hyper Surfaces for Oriented Normal Estimation of Point Clouds Qing Li, Huifang Feng, Kanle Shi, Yue Gao, Yi Fang, Yu-Shen Liu, Zhizhong Han IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [Paper][Code]
	Parts2Words: Learning Joint Embedding of Point Clouds and Texts by Bidirectional Matching between Parts and Words Chuan Tang, Xi Yang, Bojian Wu, Zhizhong Han, Yi Chang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [Paper][Code]
	NeAF: Learning Neural Angle Fields for Point Normal Estimation Shujuan Li, Junsheng Zhou, Baorui Ma, Yu-Shen Liu, Zhizhong Han (* indicates equal contribution) The AAAI Conference on Artificial Intelligence (AAAI), 2023. [Paper][Code][Project Page]
	D-Net: Learning for distinctive point clouds by self-attentive point searching and learnable feature fusion Xinhai Liu, Zhizhong Han, Sanghuk Lee, Yan-Pei Cao, Yu-Shen Liu Computer Aided Geometric Design, 2023. [Paper]

2022

	Snowflake Point Deconvolution for Point Cloud Completion and Generation with Skip-Transformer Peng Xiang, Xin Wen, Yu-Shen Liu, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Zhizhong Han IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022. [Paper][Code]
	Learning Consistency-Aware Unsigned Distance Functions Progressively from Raw Point Clouds Junsheng Zhou, Baorui Ma, Yu-Shen Liu, Yi Fang, Zhizhong Han (* indicates equal contribution) Conference on Neural Information Processing Systems (NeurIPS), 2022. [Paper][Code][Project Page]
	HSurf-Net: Normal Estimation for 3D Point Clouds by Learning Hyper Surfaces Qing Li, Yu-Shen Liu, Jin-San Cheng, Cheng Wang, Yi Fang, Zhizhong Han Conference on Neural Information Processing Systems (NeurIPS), 2022. [Paper][Code]
	Latent Partition Implicit with Surface Codes for 3D Representation Chao Chen, Yu-Shen Liu, Zhizhong Han European Conference on Computer Vision (ECCV), 2022. [Paper][Code][Project Page]
	SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction with Self-Projection Optimization Xinhai Liu, Xinchen Liu, Yu-Shen Liu, Zhizhong Han IEEE Transactions on Image Processing, 2022. [Paper]
	Surface Reconstruction from Point Clouds by Learning Predictive Context Priors Baorui Ma, Yu-Shen Liu, Matthias Zwicker, Zhizhong Han IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [Paper][Code][Project Page]
	Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors Baorui Ma, Yu-Shen Liu, Zhizhong Han IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [Paper][Code][Project Page]
	Learning Deep Implicit Functions for 3D Shapes with Dynamic Code Clouds Tianyang Li, Xin Wen, Yu-Shen Liu, Hua Su, Zhizhong Han IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [Paper][Code][Project Page]
	3D Shape Reconstruction from 2D Images with Disentangled Attribute Flow Xin Wen, Junsheng Zhou, Yu-Shen Liu, Hua Su, Zhen Dong, Zhizhong Han IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [Paper][Code]
	PMP-Net++: Point Cloud Completion by Transformer-Enhanced Multi-step Point Moving Paths Xin Wen, Peng Xiang, Zhizhong Han, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Yu-Shen Liu IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022. [Paper]

2021

	SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer Peng Xiang, Xin Wen, Yu-Shen Liu, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Zhizhong Han International Conference on Computer Vision (ICCV), 2021. (Oral presentation) [Paper][Code]
	Unsupervised Learning of Fine Structure Generation for 3D Point Clouds by 2D Projections Matching Chao Chen, Zhizhong Han*, Yu-Shen Liu, Matthias Zwicker ( indicates equal contribution) International Conference on Computer Vision (ICCV), 2021. [Paper][Code]
	Hierarchical View Predictor: Unsupervised 3D Global Feature Learning through Hierarchical Prediction among Unordered Views Zhizhong Han, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker ACM Multimedia conference (ACMMM), 2021. (Oral presentation) [Paper]
	Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces Baorui Ma, Zhizhong Han*, Yu-Shen Liu, Matthias Zwicker ( indicates equal contribution) International Conference on Machine Learning (ICML), 2021. (Spotlight) [Paper][Code]
	PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths Xin Wen, Peng Xiang, Zhizhong Han, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Yu-Shen Liu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. [Paper][Code]
	Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding Xin Wen, Zhizhong Han, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Yu-Shen Liu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. [Paper][Code]
	Fine-Grained 3D Shape Classification with Hierarchical Part-View Attentions Xinhai Liu, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker IEEE Transactions on Image Processing, 2021. [Paper][Dataset and Code][Best benchmark award in 2021!]

2020

	Point2SpatialCapsule: Aggregating Features and Spatial Relationships of Local Regions on Point Clouds using Spatial-aware Capsules Xin Wen, Zhizhong Han, Xinhai Liu, Yu-Shen Liu IEEE Transactions on Image Processing, 2020. [Paper][Code]
	Reconstructing 3D Shapes from Multiple Sketches using Direct Shape Optimization Zhizhong Han, Baorui Ma, Yu-Shen Liu, Matthias Zwicker IEEE Transactions on Image Processing, 2020. [Paper]
	CMPD: Using Cross Memory Network with Pair Discrimination for Image-Text Retrieval Xin Wen, Zhizhong Han, Yu-Shen Liu, IEEE Transactions on Circuits and Systems for Video Technology, 2020. [Paper]
	Learning to Generate Dense Point Clouds with Textures on Multiple Categories Tao Hu, Geng Lin, Zhizhong Han, Matthias Zwicker Winter Conference on Applications of Computer Vision (WACV), 2020. [Paper]
	ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker ACM Multimedia conference (ACMMM), 2020. (Oral presentation) [Paper]
	CF-SIS: Semantic-Instance Segmentation of 3D Point Clouds by Context Fusion with Self-Attention Xin Wen, Zhizhong Han, Geunhyuk Youk, Yu-Shen Liu ACM Multimedia conference (ACMMM), 2020. [Paper]
	SeqXY2SeqZ: Structure Learning for 3D Shapes by Sequentially Predicting 1D Occupancy Segments From 2D Coordinates Zhizhong Han, Guanhui Qiao, Yu-Shen Liu, Matthias Zwicker European Conference on Computer Vision (ECCV), 2020. [Paper]
	DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker International Conference on Machine Learning (ICML), 2020. [Paper][Code]
	SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization Yue Jiang, Dantong Ji, Zhizhong Han, Matthias Zwicker IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (Oral presentation) [Paper][Code]
	Point Cloud Completion by Skip-attention Network with Hierarchical Folding Wen Xin, Tianyang Li, Zhizhong Han, Yu-Shen Liu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [Paper][Code]
	3D Shape Completion with Multi-view Consistent Inference Tao Hu, Zhizhong Han, Matthias Zwicker AAAI Conference on Artificial Intelligence (AAAI), 2020. (Oral presentation) [Paper]
	LRC-Net: Learning Discriminative Features on Point Clouds by Encoding Local Region Contexts Xinhai Liu, Zhizhong Han, Fangzhou Hong, Yu-Shen Liu, Matthias Zwicker International Conference on Geometric Modeling and Processing (GMP), 2020. (Oral presentation) [Paper]

2019

	Active Arrangement of Small Objects in 3D Indoor Scenes Suiyun Zhang, Zhizhong Han, Yu-Kun Lai, Matthias Zwicker, Hui Zhang IEEE Transactions on Visualization and Computer Graphics, 2019. [Paper]
	Fast Low-rank Metric Learning for Large-scale and High-dimensional Data Han Liu, Zhizhong Han, Yu-Shen Liu, Ming Gu Conference on Neural Information Processing Systems (NeurIPS), 2019. [Paper][Code]
	Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction Zhizhong Han, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker International Conference on Computer Vision (ICCV), 2019. [Paper]
	Render4Completion: Synthesizing Multi-view Depth Maps for 3D Shape Completion Tao Hu, Zhizhong Han, Abhinav Shrivastava, Matthias Zwicker International Conference on Computer Vision (ICCV) Workshop on Geometry Meets Deep Learning, 2019. [Paper]
	L2G Auto-encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention Xinhai Liu, Zhizhong Han, Xin Wen, Yu-Shen Liu, Matthias Zwicker ACM International Conference on Multimedia (ACMMM), 2019. (Oral presentation) [Paper][Code]
	Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views Zhizhong Han, Xinhai Liu, Yu-Shen Liu, Matthias Zwicker International Joint Conference on Artificial Intelligence (IJCAI), 2019. (Oral presentation) [Paper]
	3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention Zhizhong Han, Xiyang Wang, Chi-Man Vong, Yu-Shen Liu, Matthias Zwicker, C.L.Philip Chen International Joint Conference on Artificial Intelligence (IJCAI), 2019. (Oral presentation) [Paper]
	3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN with Hierarchical Attention Aggregation Zhizhong Han, Honglei Lu, Zhenbao Liu, Chi-Man Vong, Yu-Shen Liu, Matthias Zwicker, Junwei Han, C.L.Philip Chen IEEE Transactions on Image Processing, 2019. [Paper]
	SeqViews2SeqLabels: Learning 3D Global Features via Aggregating Sequential Views by RNN with Attention Zhizhong Han, Mingyang Shang, Zhenbao Liu, Chi-Man Vong, Yu-Shen Liu, Matthias Zwicker, Junwei Han, C.L.Philip Chen IEEE Transactions on Image Processing, 2019. [Paper][Code]
	Y2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences Zhizhong Han, Mingyang Shang, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker AAAI Conference on Artificial Intelligence (AAAI), 2019. (Oral presentation) [Paper]
	View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions Zhizhong Han, Mingyang Shang, Yu-Shen Liu, Matthias Zwicker AAAI Conference on Artificial Intelligence (AAAI), 2019. (Spotlight presentation) [Paper]
	Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network Xinhai Liu, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker AAAI Conference on Artificial Intelligence (AAAI), 2019. (Oral presentation) [Paper][Code]
	Stylistic Scene Enhancement GAN: Mixed Stylistic Enhancement Generation for 3D Indoor Scenes Suiyun Zhang, Zhizhong Han, Yu-Kun Lai, Matthias Zwicker, Hui Zhang Computer Graphics International (CGI), 2019. (Oral presentation) [Paper]
	Adversarial Cross-Modal Retrieval via Learning and Transferring Single-Modal Similarities Xin Wen, Zhizhong Han, Xinyu Yin, Yu-Shen Liu IEEE International Conference on Multimedia and Expo (ICME), 2019. (Oral presentation) [Paper]
	Emotion Reinforced Visual Storytelling Nanxing Li, Bei Liu, Zhizhong Han, Yu-Shen Liu, Jianlong Fu (* indicates equal contribution) ACM International Conference on Multimedia Retrieval (ICMR), 2019. (Oral presentation) [Paper]
	Deep Learning for 3D Data Processing Zhenbao Liu, Zhizhong Han, Shuhui Bu Deep Learning in Object Detection and Recognition, Springer, Singapore, 2019, pages 155-187. [Book chapter]

2018

Deep Spatiality: Unsupervised Learning of Spatially-enhanced Global and Local 3D Features by Deep Neural Network with Coupled Softmax
Zhizhong Han, Zhenbao Liu, Chi-Man Vong, Yu-Shen Liu, Shuhui Bu, Junwei Han, C.L.Philip Chen
IEEE Transactions on Image Processing, 2018.
[Paper]

2017

	Unsupervised Learning of 3D Local Features from Raw Voxels Based on A Novel Permutation voxelization strategy Zhizhong Han, Zhenbao Liu, Junwei Han, Chi-Man Vong, Shuhui Bu, C.L.Philip Chen IEEE Transactions on Cybernetics, 2017. [Paper]
	BoSCC: Bag of Spatial Context Correlations for Spatially Enhanced 3D Shape Representation Zhizhong Han, Zhenbao Liu, Chi-Man Vong, Yu-Shen Liu, Shuhui Bu, Junwei Han, C.L.Philip Chen IEEE Transactions on Image Processing, 2017. [Paper]
	Semantic 3D Indoor Scene Enhancement Using Guide Words Suiyun Zhang, Zhizhong Han, Ralph R Martin, Hui Zhang Computer Graphics International (CGI), 2017. (Oral presentation) [Paper]
	User Guided 3D Scene Enrichment Suiyun Zhang, Zhizhong Han, Hui Zhang ACM SIGGRAPH Conference on Virtual-Reality Continuum and Its Applications in Industry, 2017. (Oral presentation) [Paper]

2016

	Unsupervised 3D Local Feature Learning by Circle Convolutional Restricted Boltzmann Machine Zhizhong Han, Zhenbao Liu, Junwei Han, Chi-Man Vong, Shuhui Bu, Xuelong Li IEEE Transactions on Image Processing, 2016. [Paper]
	Mesh Convolutional Restricted Boltzmann Machines for Unsupervised Learning of Features with Structure Preservation on 3D Meshes Zhizhong Han, Zhenbao Liu, Junwei Han, Chi-Man Vong, Shuhui Bu, C.L.Philip Chen IEEE Transactions on Neural Networks and Learning Systems, 2016. [Paper]

2014

3D Shape Creation by Style Transfer
Zhizhong Han, Zhenbao Liu, Junwei Han, Shuhui Bu
The Visual Computer, 2014.
[Paper]

2011

A New Adaptive Wavelet Transform using Lifting Scheme
Zhizhong Han, Zhenbao Liu, Yasen Xu
International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), 2011.
[Paper]