H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 37 Citations 7,218 125 World Ranking 5395 National Ranking 2643

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

The scientist’s investigation covers issues in Artificial intelligence, Recurrent neural network, Pattern recognition, Computer vision and Machine learning. His Artificial intelligence study frequently links to adjacent areas such as Construct. His work carried out in the field of Recurrent neural network brings together such families of science as End-to-end principle, Frame and Joint.

His work in the fields of Feature learning and Feature extraction overlaps with other areas such as Set. His work on JPEG, Light-field camera and Image quality as part of general Computer vision study is frequently linked to Multivariate interpolation, therefore connecting diverse disciplines of science. His research integrates issues of Ranging, Single image and Data mining in his study of Machine learning.

His most cited work include:

  • An end-to-end spatio-temporal attention model for human action recognition from skeleton data (404 citations)
  • The sixth visual object tracking VOT2018 challenge results (299 citations)
  • Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks (278 citations)

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

Wenjun Zeng focuses on Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Frame. His work in Recurrent neural network, Feature, Benchmark, Feature learning and Discriminative model are all subfields of Artificial intelligence research. The Pattern recognition study combines topics in areas such as Contextual image classification, Pyramid and Feature.

His Computer vision study incorporates themes from Detector and Code. His Machine learning study typically links adjacent topics like Key. Wenjun Zeng interconnects Margin and Robustness in the investigation of issues within Video tracking.

He most often published in these fields:

  • Artificial intelligence (78.38%)
  • Pattern recognition (28.11%)
  • Computer vision (27.57%)

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

  • Artificial intelligence (78.38%)
  • Pattern recognition (28.11%)
  • Machine learning (18.38%)

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

Artificial intelligence, Pattern recognition, Machine learning, Feature and Computer vision are his primary areas of study. His Feature learning, Discriminative model, Pose, Object detection and Re identification study are his primary interests in Artificial intelligence. Many of his research projects under Pattern recognition are closely connected to Sample with Sample, tying the diverse disciplines of science together.

The concepts of his Machine learning study are interwoven with issues in Collapse and Inference. His research on Feature also deals with topics like

  • Semantics which is related to area like Benchmark and Node,
  • Matching which connect with Ideal. Wenjun Zeng combines subjects such as Frame and Code with his study of Computer vision.

Between 2019 and 2021, his most popular works were:

  • Style Normalization and Restitution for Generalizable Person Re-Identification (46 citations)
  • Object Detection in Videos by High Quality Object Linking (38 citations)
  • A Simple Baseline for Multi-Object Tracking. (31 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

His primary areas of investigation include Artificial intelligence, Object detection, Machine learning, Pattern recognition and Computer vision. His Artificial intelligence study combines topics in areas such as Frame and Identity. His work deals with themes such as Artificial neural network, Detector and Thesaurus, which intersect with Frame.

His Pattern recognition research includes themes of Recurrent neural nets, Entropy, Entropy, Residual and Ranking. His work focuses on many connections between Computer vision and other disciplines, such as Code, that overlap with his field of interest in Contrast, Multi camera and Pose. His research investigates the connection with Semantics and areas like Feature which intersect with concerns in Benchmark, Discriminative model and Feature extraction.

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.

Best Publications

An end-to-end spatio-temporal attention model for human action recognition from skeleton data

Sijie Song;Cuiling Lan;Junliang Xing;Wenjun Zeng.
national conference on artificial intelligence (2017)

511 Citations

Benchmarking Single-Image Dehazing and Beyond

Boyi Li;Wenqi Ren;Dengpan Fu;Dacheng Tao.
IEEE Transactions on Image Processing (2019)

460 Citations

The sixth visual object tracking VOT2018 challenge results

Matej Kristan;Aleš Leonardis;Jiří Matas;Michael Felsberg.
european conference on computer vision (2019)

343 Citations

A Twofold Siamese Network for Real-Time Object Tracking

Anfeng He;Chong Luo;Xinmei Tian;Wenjun Zeng.
computer vision and pattern recognition (2018)

310 Citations

Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks

Wentao Zhu;Cuiling Lan;Junliang Xing;Wenjun Zeng.
arXiv: Computer Vision and Pattern Recognition (2016)

300 Citations

A format-compliant configurable encryption framework for access control of video

Jiangtao Wen;M. Severa;Wenjun Zeng;M.H. Luttrell.
IEEE Transactions on Circuits and Systems for Video Technology (2002)

283 Citations

View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data

Pengfei Zhang;Cuiling Lan;Junliang Xing;Wenjun Zeng.
international conference on computer vision (2017)

271 Citations

Digital image scrambling for image coding systems

Shaw-Min Lei;Wenjun Zeng.
(2000)

187 Citations

Multimedia Security Technologies for Digital Rights Management

Wenjun Zeng;Heather Yu;Ching-Yung Lin.
(2006)

169 Citations

Geometric-structure-based error concealment with novel applications in block-based low-bit-rate coding

Wenjun Zeng;Bede Liu.
IEEE Transactions on Circuits and Systems for Video Technology (1999)

161 Citations

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Best Scientists Citing Wenjun Zeng

Liang Wang

Liang Wang

Chinese Academy of Sciences

Publications: 31

Houqiang Li

Houqiang Li

University of Science and Technology of China

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Huchuan Lu

Huchuan Lu

Dalian University of Technology

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Dacheng Tao

Dacheng Tao

University of Sydney

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Jun Liu

Jun Liu

Central South University

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Wanqing Li

Wanqing Li

University of Wollongong

Publications: 25

Brant L. Candelore

Brant L. Candelore

Sony (Japan)

Publications: 25

Jiaying Liu

Jiaying Liu

Peking University

Publications: 25

Dong Liu

Dong Liu

University of Science and Technology of China

Publications: 24

Hanqing Lu

Hanqing Lu

Chinese Academy of Sciences

Publications: 23

Xiaojun Wu

Xiaojun Wu

University of Science and Technology of China

Publications: 23

Feng Wu

Feng Wu

University of Science and Technology of China

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Ling-Yu Duan

Ling-Yu Duan

Peking University

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Wengang Zhou

Wengang Zhou

University of Science and Technology of China

Publications: 20

Jingdong Wang

Jingdong Wang

Microsoft (United States)

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Haibin Ling

Haibin Ling

Stony Brook University

Publications: 19

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