H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 76 Citations 21,013 371 World Ranking 568 National Ranking 46

Research.com Recognitions

Awards & Achievements

2019 - IEEE Fellow For contributions to multimedia analysis and applications

2016 - ACM Distinguished Member

2012 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of study are Artificial intelligence, Machine learning, Convolutional neural network, Pattern recognition and Information retrieval. His work in Artificial intelligence addresses issues such as Natural language processing, which are connected to fields such as Semantics. His Machine learning research incorporates themes from Domain and Context.

The concepts of his Convolutional neural network study are interwoven with issues in Recurrent neural network, Feature learning and Inference. The various areas that Tao Mei examines in his Pattern recognition study include Image, Representation and Categorization. His research investigates the connection between Information retrieval and topics such as Ranking that intersect with issues in Visual search, Search engine, Beam search, Incremental heuristic search and Phrase search.

His most cited work include:

  • Look Closer to See Better: Recurrent Attention Convolutional Neural Network for Fine-Grained Image Recognition (576 citations)
  • Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks (478 citations)
  • MSR-VTT: A Large Video Description Dataset for Bridging Video and Language (458 citations)

What are the main themes of his work throughout his whole career to date?

Tao Mei spends much of his time researching Artificial intelligence, Machine learning, Pattern recognition, Information retrieval and Computer vision. His Artificial intelligence research focuses on Natural language processing and how it connects with Semantics. The Machine learning study combines topics in areas such as Domain, Training set and TRECVID.

His Pattern recognition study combines topics from a wide range of disciplines, such as Contextual image classification and Parsing. Tao Mei has researched Feature extraction in several fields, including Visualization and Feature. Tao Mei has included themes like Encoder, Recurrent neural network, Natural language and Speech recognition in his Closed captioning study.

He most often published in these fields:

  • Artificial intelligence (57.69%)
  • Machine learning (20.11%)
  • Pattern recognition (16.89%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (57.69%)
  • Machine learning (20.11%)
  • Pattern recognition (16.89%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Pattern recognition, Computer vision and Facial recognition system. Artificial intelligence is closely attributed to Code in his research. As part of one scientific family, Tao Mei deals mainly with the area of Machine learning, narrowing it down to issues related to the Domain, and often Feature.

His Pattern recognition research is multidisciplinary, incorporating elements of Artificial neural network, Similarity, Parsing and Generative grammar. The study incorporates disciplines such as Representation and Polygon mesh in addition to Computer vision. His biological study spans a wide range of topics, including Margin, Speech recognition and Softmax function.

Between 2019 and 2021, his most popular works were:

  • X-Linear Attention Networks for Image Captioning (49 citations)
  • Mis-Classified Vector Guided Softmax Loss for Face Recognition (19 citations)
  • FastReID: A Pytorch Toolbox for General Instance Re-identification. (16 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

Tao Mei focuses on Artificial intelligence, Discriminative model, Machine learning, Pattern recognition and Feature extraction. His work on Computer vision expands to the thematically related Artificial intelligence. His Discriminative model research integrates issues from Minimum bounding box and Code.

Tao Mei interconnects Domain, Facial recognition system and Closed captioning in the investigation of issues within Machine learning. His work on Training set as part of general Pattern recognition study is frequently linked to Dimension, therefore connecting diverse disciplines of science. Tao Mei works mostly in the field of Feature extraction, limiting it down to concerns involving Task analysis and, occasionally, Contrast and Matching.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Look Closer to See Better: Recurrent Attention Convolutional Neural Network for Fine-Grained Image Recognition

Jianlong Fu;Heliang Zheng;Tao Mei.
computer vision and pattern recognition (2017)

651 Citations

Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks

Zhaofan Qiu;Ting Yao;Tao Mei.
international conference on computer vision (2017)

597 Citations

Correlative multi-label video annotation

Guo-Jun Qi;Xian-Sheng Hua;Yong Rui;Jinhui Tang.
acm multimedia (2007)

563 Citations

MSR-VTT: A Large Video Description Dataset for Bridging Video and Language

Jun Xu;Tao Mei;Ting Yao;Yong Rui.
computer vision and pattern recognition (2016)

417 Citations

Boosting Image Captioning with Attributes

Ting Yao;Yingwei Pan;Yehao Li;Zhaofan Qiu.
international conference on computer vision (2017)

414 Citations

Multiview Spectral Embedding

Tian Xia;Dacheng Tao;Tao Mei;Yongdong Zhang.
systems man and cybernetics (2010)

407 Citations

Jointly Modeling Embedding and Translation to Bridge Video and Language

Yingwei Pan;Tao Mei;Ting Yao;Houqiang Li.
computer vision and pattern recognition (2016)

333 Citations

Personalized Recommendation Combining User Interest and Social Circle

Xueming Qian;He Feng;Guoshuai Zhao;Tao Mei.
IEEE Transactions on Knowledge and Data Engineering (2014)

320 Citations

Exploring Visual Relationship for Image Captioning

Ting Yao;Yingwei Pan;Yehao Li;Tao Mei.
european conference on computer vision (2018)

312 Citations

Learning Multi-attention Convolutional Neural Network for Fine-Grained Image Recognition

Heliang Zheng;Jianlong Fu;Tao Mei;Jiebo Luo.
international conference on computer vision (2017)

297 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing Tao Mei

Meng Wang

Meng Wang

Hefei University of Technology

Publications: 106

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 98

Dacheng Tao

Dacheng Tao

University of Sydney

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Zheng-Jun Zha

Zheng-Jun Zha

University of Science and Technology of China

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Tat-Seng Chua

Tat-Seng Chua

National University of Singapore

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Xuelong Li

Xuelong Li

Northwestern Polytechnical University

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Changsheng Xu

Changsheng Xu

Chinese Academy of Sciences

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Jiebo Luo

Jiebo Luo

University of Rochester

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Qingming Huang

Qingming Huang

Chinese Academy of Sciences

Publications: 57

Richang Hong

Richang Hong

Hefei University of Technology

Publications: 53

Jinhui Tang

Jinhui Tang

Nanjing University of Science and Technology

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Xian-Sheng Hua

Xian-Sheng Hua

Microsoft (United States)

Publications: 51

Yi Yang

Yi Yang

Zhejiang University

Publications: 50

Yongdong Zhang

Yongdong Zhang

University of Science and Technology of China

Publications: 44

Shuicheng Yan

Shuicheng Yan

National University of Singapore

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