World's Best Scientists 2026 revealed!
Yu-Gang Jiang

Yu-Gang Jiang

D-Index & Metrics

Computer Science

D-Index
81
Citations
25844
World Ranking
1028
National Ranking
146

Overview

Yu-Gang Jiang is affiliated with Fudan University in China and has a significant publication record in the field of computer science, with a particular focus on computer vision and pattern recognition and artificial intelligence. Their scholarly output demonstrates a sustained engagement with topics related to multimodal machine learning, domain adaptation, human pose and action recognition, adversarial robustness, and advanced neural network applications.

The scientist's recent papers include the following works:

  • Two-dimensional materials for next-generation computing technologies, 2020, published in Nature Nanotechnology
  • Cross-Domain Contrastive Learning for Unsupervised Domain Adaptation, 2022, published in IEEE Transactions on Multimedia
  • BEVT: BERT Pretraining of Video Transformers, 2022, presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • SVTR: Scene Text Recognition with a Single Visual Model, 2022, presented at the Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
  • Balanced Contrastive Learning for Long-Tailed Visual Recognition, 2022, presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Frequent co-authors in Yu-Gang Jiang's research include:

  • Zuxuan Wu
  • Jingjing Chen
  • Xingjun Ma
  • Yanwei Fu
  • Shaoxiang Chen

The scientist has extensively published in several venues, reflecting a presence in both conference proceedings and journals. The main publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Image Processing

Yu-Gang Jiang's research encompasses a broad range of topics within computer science and its subfields. These areas include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Signal Processing
  • Molecular Biology

Their main topics of work cover:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Adversarial Robustness in Machine Learning
  • Advanced Neural Network Applications
  • Video Analysis and Summarization
  • Advanced Image and Video Retrieval Techniques

Yu-Gang Jiang has also contributed to book publications, including a work published by Springer International Publishing titled Deep Learning for Video Understanding, scheduled for 2024.

Best Publications

  • Supervised hashing with kernels

    Wei Liu;Jun Wang;Rongrong Ji;Yu-Gang Jiang

  • Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

    Nanyang Wang;Yinda Zhang;Zhuwen Li;Yanwei Fu

  • Evaluating bag-of-visual-words representations in scene classification

    Jun Yang;Yu-Gang Jiang;Alexander G. Hauptmann;Chong-Wah Ngo

  • Towards optimal bag-of-features for object categorization and semantic video retrieval

    Yu-Gang Jiang;Chong-Wah Ngo;Jun Yang

  • DSOD: Learning Deeply Supervised Object Detectors from Scratch

    Zhiqiang Shen;Zhuang Liu;Jianguo Li;Yu-Gang Jiang

  • The THUMOS challenge on action recognition for videos “in the wild”

    Haroon Idrees;Amir Roshan Zamir;Yu-Gang Jiang;Alex Gorban

  • NAIS: Neural Attentive Item Similarity Model for Recommendation

    Xiangnan He;Zhankui He;Jingkuan Song;Zhenguang Liu

  • Modeling Spatial-Temporal Clues in a Hybrid Deep Learning Framework for Video Classification

    Zuxuan Wu;Xi Wang;Yu-Gang Jiang;Hao Ye

  • Learning Fashion Compatibility with Bidirectional LSTMs

    Xintong Han;Zuxuan Wu;Yu-Gang Jiang;Larry S. Davis

  • Pose-Normalized Image Generation for Person Re-identification

    Xuelin Qian;Yanwei Fu;Tao Xiang;Wenxuan Wang

  • Multi-Level Semantic Feature Augmentation for One-Shot Learning

    Zitian Chen;Yanwei Fu;Yinda Zhang;Yu-Gang Jiang

  • The MediaMill TRECVID 2011 Semantic Video Search Engine

    C. G. M. Snoek;K. E. A. van de Sande;X. Li;M. Mazloom

  • Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks

    Yu-Gang Jiang;Zuxuan Wu;Jun Wang;Xiangyang Xue

  • Consumer video understanding: a benchmark database and an evaluation of human and machine performance

    Yu-Gang Jiang;Guangnan Ye;Shih-Fu Chang;Daniel Ellis

  • WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection

    Bojia Zi;Minghao Chang;Jingjing Chen;Xingjun Ma

  • Representations of Keypoint-Based Semantic Concept Detection: A Comprehensive Study

    Yu-Gang Jiang;Jun Yang;Chong-Wah Ngo;A.G. Hauptmann

  • Multi-scale Deep Learning Architectures for Person Re-identification

    Xuelin Qian;Yanwei Fu;Yu-Gang Jiang;Tao Xiang

  • Recurrent Fusion Network for Image Captioning

    Wenhao Jiang;Lin Ma;Yu-Gang Jiang;Wei Liu

  • Trajectory-Based modeling of human actions with motion reference points

    Yu-Gang Jiang;Qi Dai;Xiangyang Xue;Wei Liu

  • M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection.

    Junke Wang;Zuxuan Wu;Jingjing Chen;Yu-Gang Jiang

  • High-Level Event Recognition in Unconstrained Videos

    Yu-Gang Jiang;Subhabrata Bhattacharya;Shih-Fu Chang;Mubarak Shah

Frequent Co-Authors

Xiangyang Xue
Xiangyang Xue Fudan University
Yanwei Fu
Yanwei Fu Fudan University
Chong-Wah Ngo
Chong-Wah Ngo Singapore Management University
Zuxuan Wu
Zuxuan Wu Fudan University
Shih-Fu Chang
Shih-Fu Chang Columbia University
Wei Liu
Wei Liu Tencent (China)
Leonid Sigal
Leonid Sigal University of British Columbia
Tat-Seng Chua
Tat-Seng Chua National University of Singapore
Larry S. Davis
Larry S. Davis University of Maryland, College Park
Jinhui Tang
Jinhui Tang Nanjing University of Science and Technology

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