World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
66
Citations
33131
World Ranking
2253
National Ranking
311

Overview

Xinggang Wang is affiliated with Huazhong University of Science and Technology in China. Their research centers on computer science and engineering, with a significant focus on computer vision and pattern recognition.

Their publication record includes papers in prominent journals and conferences, covering a span from 2020 to 2024. Notable recent works include:

  • Deep High-Resolution Representation Learning for Visual Recognition, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT, 2020, IEEE Transactions on Medical Imaging
  • CCNet: Criss-Cross Attention for Semantic Segmentation, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model, 2024, arXiv (Cornell University)

Their research interests encompass several main topics and subfields, including:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Aerospace Engineering
  • Biomedical Engineering
  • Radiology, Nuclear Medicine and Imaging

Key research themes in their work involve:

  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Domain Adaptation and Few-Shot Learning
  • Video Surveillance and Tracking Methods
  • Human Pose and Action Recognition
  • Multimodal Machine Learning Applications
  • Advanced Vision and Imaging

Wang frequently collaborates with a group of coauthors, including:

  • Wenyu Liu
  • Tianheng Cheng
  • Jiemin Fang
  • Shaoyu Chen
  • Qian Zhang

Their research outputs appear predominantly in venues such as:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Image and Vision Computing
  • International Journal of Computer Vision

Their work contributes broadly to advancing methodologies in neural networks and image processing technologies, with applications spanning medical imaging and visual recognition tasks.

Best Publications

  • Deep High-Resolution Representation Learning for Visual Recognition

    Jingdong Wang;Ke Sun;Tianheng Cheng;Borui Jiang

  • CCNet: Criss-Cross Attention for Semantic Segmentation

    Zilong Huang;Xinggang Wang;Lichao Huang;Chang Huang

  • ByteTrack: Multi-Object Tracking by Associating Every Detection Box

    Unknown

  • FairMOT: On the Fairness of Detection and Re-identification in Multiple Object Tracking

    Yifu Zhang;Chunyu Wang;Xinggang Wang;Wenjun Zeng

  • CCNet: Criss-Cross Attention for Semantic Segmentation

    Zilong Huang;Xinggang Wang;Yunchao Wei;Lichao Huang

  • Mask Scoring R-CNN

    Zhaojin Huang;Lichao Huang;Yongchao Gong;Chang Huang

  • TextBoxes: a fast text detector with a single deep neural network

    Minghui Liao;Baoguang Shi;Xiang Bai;Xinggang Wang

  • ASTER: An Attentional Scene Text Recognizer with Flexible Rectification

    Baoguang Shi;Mingkun Yang;Xinggang Wang;Pengyuan Lyu

  • High-Resolution Representations for Labeling Pixels and Regions

    Ke Sun;Yang Zhao;Borui Jiang;Tianheng Cheng

  • Robust Scene Text Recognition with Automatic Rectification

    Baoguang Shi;Xinggang Wang;Pengyuan Lyu;Cong Yao

  • DeepContour: A deep convolutional feature learned by positive-sharing loss for contour detection

    Wei Shen;Xinggang Wang;Yan Wang;Xiang Bai

  • EVA: Exploring the Limits of Masked Visual Representation Learning at Scale

    Unknown

  • A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT

    Xinggang Wang;Xianbo Deng;Qing Fu;Qiang Zhou

  • Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing

    Zilong Huang;Xinggang Wang;Jiasi Wang;Wenyu Liu

  • YOLO-World: Real-Time Open-Vocabulary Object Detection

    Unknown

  • YOLOP: You Only Look Once for Panoptic Driving Perception

    Unknown

  • Multiple Instance Detection Network with Online Instance Classifier Refinement

    Peng Tang;Xinggang Wang;Xiang Bai;Wenyu Liu

  • Revisiting multiple instance neural networks

    Xinggang Wang;Yongluan Yan;Peng Tang;Xiang Bai

  • Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-Identification

    Cheng Wang;Qian Zhang;Chang Huang;Wenyu Liu

  • PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

    Peng Tang;Xinggang Wang;Song Bai;Wei Shen

  • Unsupervised Domain Adaptive Re-Identification: Theory and Practice

    Liangchen Song;Cheng Wang;Lefei Zhang;Bo Du

  • Traffic sign detection and recognition using fully convolutional network guided proposals

    Yingying Zhu;Chengquan Zhang;Duoyou Zhou;Xinggang Wang

  • Automated defect inspection of LED chip using deep convolutional neural network

    Hui Lin;Bin Li;Xinggang Wang;Yufeng Shu

  • Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning

    Xinggang Wang;Wei Yang;Jeffrey Weinreb;Juan Han

Frequent Co-Authors

Wenyu Liu
Wenyu Liu Huazhong University of Science and Technology
Xiang Bai
Xiang Bai Huazhong University of Science and Technology
Chang Huang
Chang Huang Horizon Robotics Inc.
Cong Yao
Cong Yao Alibaba Group (China)
Zhuowen Tu
Zhuowen Tu University of California, San Diego
Song Bai
Song Bai ByteDance
Jingdong Wang
Jingdong Wang Baidu (China)
Longin Jan Latecki
Longin Jan Latecki Temple University
Wenjun Zeng
Wenjun Zeng Microsoft (United States)
Wei Shen
Wei Shen Johns Hopkins University

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