H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 70 Citations 18,593 393 World Ranking 858 National Ranking 73

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Changsheng Xu spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Video tracking and Feature extraction. His Artificial intelligence research includes elements of Time complexity and Machine learning. His work investigates the relationship between Computer vision and topics such as Identification that intersect with problems in Viterbi algorithm.

His Pattern recognition study incorporates themes from Facial recognition system, Face, Feature and Subspace topology. His Video tracking research is multidisciplinary, incorporating perspectives in Image processing, Object detection, Multimedia and Automatic summarization. The various areas that Changsheng Xu examines in his Feature extraction study include Contextual image classification, Discriminative model, Music information retrieval and Cluster analysis.

His most cited work include:

  • The Visual Object Tracking VOT2016 Challenge Results (462 citations)
  • The sixth visual object tracking VOT2018 challenge results (299 citations)
  • The Visual Object Tracking VOT2017 Challenge Results (285 citations)

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

His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Feature extraction. His Artificial intelligence study often links to related topics such as Natural language processing. In his study, Information retrieval is strongly linked to Visualization, which falls under the umbrella field of Pattern recognition.

His work carried out in the field of Machine learning brings together such families of science as Classifier and Social media. His research investigates the connection between Feature extraction and topics such as Speech recognition that intersect with issues in Audio signal processing and Automatic summarization. His Video tracking study deals with Multimedia intersecting with Personalization.

He most often published in these fields:

  • Artificial intelligence (59.83%)
  • Pattern recognition (25.05%)
  • Computer vision (20.30%)

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

  • Artificial intelligence (59.83%)
  • Pattern recognition (25.05%)
  • Representation (7.34%)

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

His primary areas of investigation include Artificial intelligence, Pattern recognition, Representation, Natural language processing and Image. As a member of one scientific family, he mostly works in the field of Artificial intelligence, focusing on Machine learning and, on occasion, Graph neural networks. His biological study spans a wide range of topics, including Visualization, Feature and Joint.

His Representation study integrates concerns from other disciplines, such as Embedding and Information retrieval. His study in Natural language processing is interdisciplinary in nature, drawing from both Adversarial system, The Internet and Search engine. His Image research incorporates elements of Task, Word and Human–computer interaction.

Between 2019 and 2021, his most popular works were:

  • Dynamic Refinement Network for Oriented and Densely Packed Object Detection (17 citations)
  • Geometry Guided Pose-Invariant Facial Expression Recognition (9 citations)
  • Density-Aware Multi-Task Learning for Crowd Counting (7 citations)

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

  • Artificial intelligence
  • Machine learning
  • The Internet

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Semantics, Feature extraction and Deep learning. In general Artificial intelligence study, his work on Visualization often relates to the realm of Task analysis, thereby connecting several areas of interest. His Pattern recognition research incorporates themes from Contextual image classification and Benchmark.

His work in Semantics tackles topics such as Information retrieval which are related to areas like User modeling. His work deals with themes such as Detector, Feature, Object detection and Facial recognition system, Face, which intersect with Feature extraction. His Deep learning research integrates issues from Facial expression recognition, Image synthesis, Training set and Geometry, Invariant.

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

The Visual Object Tracking VOT2016 Challenge Results

Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg.
european conference on computer vision (2016)

1423 Citations

The Visual Object Tracking VOT2017 Challenge Results

Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg.
international conference on computer vision (2017)

1389 Citations

Street-to-shop: cross-scenario clothing retrieval via parts alignment and auxiliary set

Si Liu;Zheng Song;Meng Wang;Changsheng Xu.
acm multimedia (2012)

357 Citations

Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set

Si Liu;Zheng Song;Guangcan Liu;Changsheng Xu.
computer vision and pattern recognition (2012)

351 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

Multi-task Correlation Particle Filter for Robust Object Tracking

Tianzhu Zhang;Changsheng Xu;Ming-Hsuan Yang.
computer vision and pattern recognition (2017)

329 Citations

Hi, magic closet, tell me what to wear!

Si Liu;Jiashi Feng;Zheng Song;Tianzhu Zhang.
acm multimedia (2012)

276 Citations

A mid-level representation framework for semantic sports video analysis

Ling-Yu Duan;Min Xu;Tat-Seng Chua;Qi Tian.
acm multimedia (2003)

269 Citations

A unified framework for semantic shot classification in sports video

Ling-Yu Duan;Min Xu;Qi Tian;Chang-Sheng Xu.
IEEE Transactions on Multimedia (2005)

265 Citations

Deep Representation Learning With Part Loss for Person Re-Identification

Hantao Yao;Shiliang Zhang;Richang Hong;Yongdong Zhang.
IEEE Transactions on Image Processing (2019)

231 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 Changsheng Xu

Qingming Huang

Qingming Huang

Chinese Academy of Sciences

Publications: 92

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 89

Shuicheng Yan

Shuicheng Yan

National University of Singapore

Publications: 75

Hanqing Lu

Hanqing Lu

Chinese Academy of Sciences

Publications: 61

Tao Mei

Tao Mei

Jingdong (China)

Publications: 37

Si Liu

Si Liu

Beihang University

Publications: 36

Meng Wang

Meng Wang

Hefei University of Technology

Publications: 34

Xiaochun Cao

Xiaochun Cao

Chinese Academy of Sciences

Publications: 34

Wen Gao

Wen Gao

Peking University

Publications: 33

Liang Lin

Liang Lin

Sun Yat-sen University

Publications: 32

Shuqiang Jiang

Shuqiang Jiang

Chinese Academy of Sciences

Publications: 32

Huchuan Lu

Huchuan Lu

Dalian University of Technology

Publications: 30

Jing Liu

Jing Liu

Chinese Academy of Sciences

Publications: 28

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 27

Jiebo Luo

Jiebo Luo

University of Rochester

Publications: 27

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