World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
8439
World Ranking
10532
National Ranking
4414

Overview

Xuming He is affiliated with Washington University in St. Louis in the United States. Their research primarily spans the fields of Computer Science and Engineering, with significant contributions in subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Statistics and Probability, and Control and Systems Engineering.

The scientist has focused on several main topics within their research, including Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning, Advanced Image and Video Retrieval Techniques, Advanced Neural Network Applications, Human Pose and Action Recognition, Neural Networks and Reservoir Computing, and Optical Network Technologies.

Recent papers authored or co-authored by Xuming He cover diverse areas across computer vision, AI, and computational methods. These include:

  • SGTR: End-to-end Scene Graph Generation with Transformer, 2022, published in the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Learning Cross-Modal Context Graph for Visual Grounding, 2020, published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • CALIP: Zero-Shot Enhancement of CLIP with Parameter-Free Attention, 2023, published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • DeepPhospho accelerates DIA phosphoproteome profiling through in silico library generation, 2021, published in Nature Communications
  • Deep photonic reservoir computing recurrent network, 2023, published in Optica

Xuming He frequently collaborates with several co-authors, including Songyang Zhang, Chuyu Zhang, Jingyi Yu, Rongjie Li, and Cheng Wang. These collaborations have contributed to multiple publications spanning various topics within AI and engineering.

The scientist's work appears regularly in well-regarded publication venues. The most frequent outlets include arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), APL Machine Learning, and the 2022 IEEE Power & Energy Society General Meeting (PESGM).

Collectively, Xuming He's research integrates methods in artificial intelligence, deep learning, and multimodal applications with a particular emphasis on advancing techniques in computer vision and neural network architectures.

Best Publications

  • Multiscale conditional random fields for image labeling

    Xuming He;R.S. Zemel;M.A. Carreira-Perpinan

  • DER: Dynamically Expandable Representation for Class Incremental Learning

    Shipeng Yan;Jiangwei Xie;Xuming He

  • Learning and Incorporating Top-Down Cues in Image Segmentation

    Xuming He;Richard S. Zemel;Debajyoti Ray

  • Discrete-Continuous Depth Estimation from a Single Image

    Miaomiao Liu;Mathieu Salzmann;Xuming He

  • Part-aware Prototype Network for Few-shot Semantic Segmentation

    Yongfei Liu;Xiangyi Zhang;Songyang Zhang;Xuming He

  • Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images

    Shuailin Li;Chuyu Zhang;Xuming He

  • Distribution Alignment: A Unified Framework for Long-tail Visual Recognition

    Songyang Zhang;Zeming Li;Shipeng Yan;Xuming He

  • Learning and incorporating top-down cues in image segmentation

    Xuming He;Richard S. Zemel;Debajyoti Ray

  • Forest Change Detection in Incomplete Satellite Images With Deep Neural Networks

    Salman H. Khan;Xuming He;Fatih Porikli;Mohammed Bennamoun

  • Pose-Aware Multi-Level Feature Network for Human Object Interaction Detection

    Bo Wan;Desen Zhou;Yongfei Liu;Rongjie Li

  • Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation

    Rongjie Li;Songyang Zhang;Bo Wan;Xuming He

  • SentiCap: generating image descriptions with sentiments

    Alexander Mathews;Lexing Xie;Xuming He

  • Boundary-Aware Instance Segmentation

    Zeeshan Hayder;Xuming He;Mathieu Salzmann

  • Indoor scene structure analysis for single image depth estimation

    Wei Zhuo;Mathieu Salzmann;Xuming He;Miaomiao Liu

  • SemStyle: Learning to Generate Stylised Image Captions Using Unaligned Text

    Alexander Mathews;Lexing Xie;Xuming He

  • SGTR: End-to-end Scene Graph Generation with Transformer

    Unknown

  • Multiclass semantic video segmentation with object-level active inference

    Buyu Liu;Xuming He

  • Dynamic Context Correspondence Network for Semantic Alignment

    Shuaiyi Huang;Qiuyue Wang;Songyang Zhang;Shipeng Yan

  • CALIP: Zero-Shot Enhancement of CLIP with Parameter-Free Attention

    Unknown

  • Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition

    Tailin Chen;Desen Zhou;Jian Wang;Shidong Wang

  • Robust Face Alignment Under Occlusion via Regional Predictive Power Estimation

    Heng Yang;Xuming He;Xuhui Jia;Ioannis Patras

  • Geometry-Aware Deep Network for Single-Image Novel View Synthesis

    Miaomiao Liu;Xuming He;Mathieu Salzmann

  • Shape-Aware Semi-supervised 3D Semantic Segmentation for Medical Images

    Shuailin Li;Chuyu Zhang;Xuming He

  • Learning Cross-Modal Context Graph for Visual Grounding

    Yongfei Liu;Bo Wan;Xiaodan Zhu;Xuming He

  • LatentGNN: Learning Efficient Non-local Relations for Visual Recognition

    Songyang Zhang;Shipeng Yan;Xuming He

Frequent Co-Authors

Nick Barnes
Nick Barnes Australian National University
Mathieu Salzmann
Mathieu Salzmann École Polytechnique Fédérale de Lausanne
Fatih Porikli
Fatih Porikli Australian National University
Lexing Xie
Lexing Xie Australian National University
Elinor McKone
Elinor McKone Australian National University
Hongdong Li
Hongdong Li Australian National University
Richard S. Zemel
Richard S. Zemel University of Toronto
Stephen Gould
Stephen Gould Australian National University
Alan L. Yuille
Alan L. Yuille Johns Hopkins University
Mohammed Bennamoun
Mohammed Bennamoun University of Western Australia

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Looking for flexible ways to launch your Computer Science journey? Many students consider 1 year associate degree programs online to quickly gain foundational skills. These accelerated options let you start working or continue to a bachelor’s degree sooner.

Affordability matters, especially for international or budget-conscious students. Exploring the cheapest online degrees can help you minimize student debt while getting a quality education. Many accredited programs now offer competitive tuition for online learners.

Worried about your academic record? Some college that accepts low gpa can provide you with a second chance, offering admission pathways even if your GPA is below average. This opens doors to new opportunities in the tech field.

Interested in expanding your career options? While a Computer Science degree leads to numerous high-demand jobs, you can also learn about high-paying jobs with environmental science degree to diversify your skills and professional pathways. Many tech skills are transferable across industries, boosting your long-term potential.

Best Scientists Citing Xuming He

Trending Scientists

Recently Published Articles