World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
8932
World Ranking
5923
National Ranking
787

Overview

Zhiguo Cao is affiliated with Huazhong University of Science and Technology in China. Their research primarily centers on the fields of Computer Science and Engineering, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Aerospace Engineering, and Computational Mechanics.

The scientist has produced a significant body of work, publishing extensively in topics that include Advanced Vision and Imaging, Video Surveillance and Tracking Methods, Advanced Image Processing Techniques, Advanced Image and Video Retrieval Techniques, Human Pose and Action Recognition, Image Processing Techniques and Applications, and Advanced Neural Network Applications.

Zhiguo Cao's research outputs appear in a variety of publication venues. Frequent venues include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Circuits and Systems for Video Technology

Some of the recent papers authored by Zhiguo Cao are:

  • An interpretable mortality prediction model for COVID-19 patients, 2020, Nature Machine Intelligence
  • A machine learning-based model for survival prediction in patients with severe COVID-19 infection, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • Interior Attention-Aware Network for Infrared Small Target Detection, 2022, IEEE Transactions on Geoscience and Remote Sensing
  • Decoupled Two-Stage Crowd Counting and Beyond, 2021, IEEE Transactions on Image Processing
  • Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Zhiguo Cao collaborates frequently with a number of researchers including Hao Lü, Ke Xian, Yang Xiao, Juewen Peng, and Zhiyu Pan. These collaborations have resulted in numerous joint publications.

Best Publications

  • An interpretable mortality prediction model for COVID-19 patients

    Li Yan;Hai Tao Zhang;Jorge Goncalves;Yang Xiao

  • A machine learning-based model for survival prediction in patients with severe COVID-19 infection

    Yan L;Zhang H;Goncalves J;Xiao Y

  • TasselNet: counting maize tassels in the wild via local counts regression network

    Hao Lu;Zhiguo Cao;Yang Xiao;Bohan Zhuang

  • VisDrone-DET2020: The Vision Meets Drone Object Detection in Image Challenge Results.

    Dawei Du;Longyin Wen;Pengfei Zhu;Heng Fan

  • A fast and robust local descriptor for 3D point cloud registration

    Jiaqi Yang;Zhiguo Cao;Qian Zhang

  • Monocular Relative Depth Perception with Web Stereo Data Supervision

    Ke Xian;Chunhua Shen;Zhiguo Cao;Hao Lu

  • From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer

    Haipeng Xiong;Hao Lu;Chengxin Liu;Liang Liu

  • A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation From a Single Depth Image

    Fu Xiong;Boshen Zhang;Yang Xiao;Zhiguo Cao

  • Structure-Guided Ranking Loss for Single Image Depth Prediction

    Ke Xian;Jianming Zhang;Oliver Wang;Long Mai

  • Automatic image-based detection technology for two critical growth stages of maize: Emergence and three-leaf stage

    Zhenghong Yu;Zhiguo Cao;Xi Wu;Xiaodong Bai

  • TOLDI: An effective and robust approach for 3D local shape description

    Jiaqi Yang;Qian Zhang;Yang Xiao;Zhiguo Cao

  • P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds

    Haozhe Qi;Chen Feng;Zhiguo Cao;Feng Zhao

  • Crop segmentation from images by morphology modeling in the CIE L*a*b* color space

    X. D. Bai;Z. G. Cao;Y. Wang;Z. H. Yu

  • TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks

    Haipeng Xiong;Zhiguo Cao;Hao Lu;Simon Madec

  • Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting

    Unknown

  • DeepCloud: Ground-Based Cloud Image Categorization Using Deep Convolutional Features

    Liang Ye;Zhiguo Cao;Yang Xiao

  • NM-Net: Mining Reliable Neighbors for Robust Feature Correspondences

    Chen Zhao;Zhiguo Cao;Chi Li;Xin Li

  • In-field automatic observation of wheat heading stage using computer vision

    Yanjun Zhu;Zhiguo Cao;Hao Lu;Yanan Li

  • Action Recognition for Depth Video using Multi-view Dynamic Images

    Yang Xiao;Jun Chen;Yancheng Wang;Zhiguo Cao

  • 3DV: 3D Dynamic Voxel for Action Recognition in Depth Video

    Yancheng Wang;Yang Xiao;Fu Xiong;Wenxiang Jiang

  • An Embarrassingly Simple Approach to Visual Domain Adaptation

    Hao Lu;Chunhua Shen;Zhiguo Cao;Yang Xiao

  • NTIRE 2019 Challenge on Real Image Denoising: Methods and Results

    Abdelrahman Abdelhamed;Radu Timofte;Michael S. Brown;Songhyun Yu

  • Deep Attention-Based Classification Network for Robust Depth Prediction

    Ruibo Li;Ke Xian;Chunhua Shen;Zhiguo Cao

Frequent Co-Authors

Chunhua Shen
Chunhua Shen Zhejiang University
Joey Tianyi Zhou
Joey Tianyi Zhou Agency for Science, Technology and Research
Junsong Yuan
Junsong Yuan University at Buffalo, State University of New York
Armin B. Cremers
Armin B. Cremers University of Bonn
Hai-Tao Zhang
Hai-Tao Zhang Huazhong University of Science and Technology
xin li
xin li Louisiana State University
Lei Zhu
Lei Zhu Tongji University
Radu Timofte
Radu Timofte University of Wurzburg
Anton van den Hengel
Anton van den Hengel University of Adelaide
Shugong Xu
Shugong Xu Shanghai University

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