World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
6374
World Ranking
12018
National Ranking
1486

Overview

Gang Zeng is affiliated with Peking University in China and specializes in research primarily within the fields of Computer Science and Engineering. Their work encompasses a range of subfields including Computer Vision and Pattern Recognition, Computational Mechanics, Computer Graphics and Computer-Aided Design, Aerospace Engineering, and Geology.

The scientist's research covers several main topics, with a particular focus on 3D Shape Modeling and Analysis, Computer Graphics and Visualization Techniques, Advanced Vision and Imaging, and Advanced Neural Network Applications. Additional areas of interest include Robotics and Sensor-Based Localization, 3D Surveying and Cultural Heritage, and Image Processing and 3D Reconstruction.

Gang Zeng has contributed to multiple recent publications, including:

  • Context Autoencoder for Self-supervised Representation Learning, 2023, International Journal of Computer Vision
  • Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision, 2021, arXiv (Cornell University)
  • Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation, 2020, arXiv (Cornell University)
  • MaskGroup: Hierarchical Point Grouping and Masking for 3D Instance Segmentation, 2022, 2022 IEEE International Conference on Multimedia and Expo (ICME)
  • Not All Voxels Are Equal: Semantic Scene Completion from the Point-Voxel Perspective, 2022, Proceedings of the AAAI Conference on Artificial Intelligence

Their collaborative efforts frequently involve coauthors such as Xiaokang Chen, Jingbo Wang, Jiaxiang Tang, and Ruijie Lu.

Gang Zeng's publications have appeared predominantly in venues like:

  • arXiv (Cornell University)
  • International Journal of Computer Vision
  • 2022 IEEE International Conference on Multimedia and Expo (ICME)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Best Publications

  • Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision

    Xiaokang Chen;Yuhui Yuan;Gang Zeng;Jingdong Wang

  • Image-based procedural modeling of facades

    Pascal Müller;Gang Zeng;Peter Wonka;Luc Van Gool

  • Context Autoencoder for Self-Supervised Representation Learning

    Unknown

  • Image-based plant modeling

    Long Quan;Ping Tan;Gang Zeng;Lu Yuan

  • Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation

    Xiaokang Chen;Kwan-Yee Lin;Jingbo Wang;Wayne Wu

  • Image-based tree modeling

    Ping Tan;Gang Zeng;Jingdong Wang;Sing Bing Kang

  • Image-based procedural modeling of facades

    Unknown

  • Complementary hashing for approximate nearest neighbor search

    Hao Xu;Jingdong Wang;Zhu Li;Gang Zeng

  • Scalable k-NN graph construction for visual descriptors

    Jing Wang;Jingdong Wang;Gang Zeng;Zhuowen Tu

  • Structure-Sensitive Superpixels via Geodesic Distance

    Peng Wang;Gang Zeng;Rui Gan;Jingdong Wang

  • Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignment

    Unknown

  • Image-based tree modeling

    Unknown

  • 3D Sketch-Aware Semantic Scene Completion via Semi-Supervised Structure Prior

    Xiaokang Chen;Kwan-Yee Lin;Chen Qian;Gang Zeng

  • Neural Style Transfer via Meta Networks

    Falong Shen;Shuicheng Yan;Gang Zeng

  • Fast approximate k-means via cluster closures

    Jing Wang;Jingdong Wang;Qifa Ke;Gang Zeng

  • Salient object detection for searched web images via global saliency

    Peng Wang;Jingdong Wang;Gang Zeng;Jie Feng

  • Optimizing kd-trees for scalable visual descriptor indexing

    You Jia;Jingdong Wang;Gang Zeng;Hongbin Zha

  • Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF

    Falong Shen;Rui Gan;Shuicheng Yan;Gang Zeng

  • Trinary-Projection Trees for Approximate Nearest Neighbor Search

    Jingdong Wang;Naiyan Wang;You Jia;Jian Li

  • Joint Implicit Image Function for Guided Depth Super-Resolution

    Jiaxiang Tang;Xiaokang Chen;Gang Zeng

  • Progressive surface reconstruction from images using a local prior

    Gang Zeng;S. Paris;L. Quan;F. Sillion

  • Similarity-Aware Patchwork Assembly for Depth Image Super-resolution

    Jing Li;Zhichao Lu;Gang Zeng;Rui Gan

  • Towards mass-produced building models

    Luc Van Gool;Gang Zeng;Filip Van den Borre;Pascal Müller

  • Supervised Kernel Descriptors for Visual Recognition

    Peng Wang;Jingdong Wang;Gang Zeng;Weiwei Xu

  • Structure-sensitive superpixels via geodesic distance

    Gang Zeng;Peng Wang;Jingdong Wang;Rui Gan

Frequent Co-Authors

Jingdong Wang
Jingdong Wang Baidu (China)
Hongbin Zha
Hongbin Zha Peking University
Long Quan
Long Quan Hong Kong University of Science and Technology
Shipeng Li
Shipeng Li Chinese University of Hong Kong, Shenzhen
Sylvain Paris
Sylvain Paris Adobe Systems (United States)
Long Wang
Long Wang Peking University
Peng Wang
Peng Wang Baidu (China)
Hongsheng Li
Hongsheng Li Chinese University of Hong Kong
Zhuowen Tu
Zhuowen Tu University of California, San Diego
François X. Sillion
François X. Sillion French Institute for Research in Computer Science and Automation - INRIA

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

Exploring computer science opens many doors, but related online degrees can expand your opportunities even further. Those interested in sustainability might wonder, what can you do with an environmental science major? Careers include environmental consulting, policy advising, and research—fields increasingly reliant on data analysis and technical skills.

If you prefer a flexible study schedule, an online computer science degree lets you gain in-demand skills quickly. These programs cater to those eager to enter the workforce or upskill without pausing their current commitments.

There are also many options in engineering. If you’re passionate about the environment, consider an environmental engineer degree online. For a broader technical foundation, online mechanical engineering degrees prepare students for roles in design, manufacturing, and robotics.

Whether you aim for technology, engineering, or environmental fields, these related online degrees and pathways offer flexible and affordable education options, allowing you to customize your career journey.

Best Scientists Citing Gang Zeng

Trending Scientists