D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 68 Citations 22,375 203 World Ranking 974 National Ranking 20

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

His primary areas of study are Artificial intelligence, Pattern recognition, Feature extraction, Machine learning and Convolutional neural network. His work in Object detection, Discriminative model, Artificial neural network, Feature and Deep learning are all subfields of Artificial intelligence research. He interconnects Segmentation, Categorization and Benchmark in the investigation of issues within Object detection.

His Feature extraction study combines topics from a wide range of disciplines, such as Feature and Training set. His biological study spans a wide range of topics, including Pose, Task and Salience. His studies in Convolutional neural network integrate themes in fields like Contextual image classification, Eye tracking, Robustness and Conditional random field.

His most cited work include:

  • Unsupervised Salience Learning for Person Re-identification (794 citations)
  • Visual Tracking with Fully Convolutional Networks (771 citations)
  • Saliency detection by multi-context deep learning (689 citations)

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

Wanli Ouyang focuses on Artificial intelligence, Pattern recognition, Object detection, Computer vision and Machine learning. Artificial intelligence is represented through his Feature, Convolutional neural network, Feature extraction, Artificial neural network and Deep learning research. His Pattern recognition research includes themes of Pose and Benchmark.

His Object detection research incorporates themes from Pascal, Minimum bounding box and Message passing. His Image, Video tracking and Data compression study in the realm of Computer vision interacts with subjects such as Frame and Pedestrian detection. His work in the fields of Machine learning, such as Re identification, intersects with other areas such as Key.

He most often published in these fields:

  • Artificial intelligence (85.02%)
  • Pattern recognition (40.77%)
  • Object detection (22.65%)

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

  • Artificial intelligence (85.02%)
  • Pattern recognition (40.77%)
  • Machine learning (20.91%)

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

Wanli Ouyang mainly investigates Artificial intelligence, Pattern recognition, Machine learning, Computer vision and Feature. His research related to Object detection, Object, Artificial neural network, Benchmark and Image might be considered part of Artificial intelligence. His Pattern recognition research is multidisciplinary, relying on both Pose and Equalization.

His study on Proxy is often connected to Key, Matching, Architecture and One shot as part of broader study in Machine learning. His work on Data compression and Monocular as part of general Computer vision research is frequently linked to Detector, Frame and Encoder, thereby connecting diverse disciplines of science. The Feature study combines topics in areas such as Pixel, Contrast, Convolutional neural network and Feature extraction.

Between 2019 and 2021, his most popular works were:

  • Deep Learning for Generic Object Detection: A Survey (461 citations)
  • Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition (43 citations)
  • Equalization Loss for Long-Tailed Object Recognition (41 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Wanli Ouyang spends much of his time researching Artificial intelligence, Pattern recognition, Machine learning, Object detection and Benchmark. Wanli Ouyang usually deals with Artificial intelligence and limits it to topics linked to Computer vision and Pairwise comparison. His study focuses on the intersection of Pattern recognition and fields such as Pose with connections in the field of Clustering coefficient.

His Machine learning study incorporates themes from Relation and Redundancy. His research integrates issues of Pascal, Hierarchical search, Computation and Data mining in his study of Object detection. The concepts of his Benchmark study are interwoven with issues in Representation, Coordinate system, Channel, Boosting and Task.

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

Unsupervised Salience Learning for Person Re-identification

Rui Zhao;Wanli Ouyang;Xiaogang Wang.
computer vision and pattern recognition (2013)

1044 Citations

Visual Tracking with Fully Convolutional Networks

Lijun Wang;Wanli Ouyang;Xiaogang Wang;Huchuan Lu.
international conference on computer vision (2015)

852 Citations

Saliency detection by multi-context deep learning

Rui Zhao;Wanli Ouyang;Hongsheng Li;Xiaogang Wang.
computer vision and pattern recognition (2015)

711 Citations

Joint Deep Learning for Pedestrian Detection

Wanli Ouyang;Xiaogang Wang.
international conference on computer vision (2013)

626 Citations

Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification

Tong Xiao;Hongsheng Li;Wanli Ouyang;Xiaogang Wang.
computer vision and pattern recognition (2016)

612 Citations

Deep Learning for Generic Object Detection: A Survey

Li Liu;Li Liu;Wanli Ouyang;Xiaogang Wang;Paul W. Fieguth.
International Journal of Computer Vision (2020)

601 Citations

Learning Mid-level Filters for Person Re-identification

Rui Zhao;Wanli Ouyang;Xiaogang Wang.
computer vision and pattern recognition (2014)

574 Citations

Person Re-identification by Salience Matching

Rui Zhao;Wanli Ouyang;Xiaogang Wang.
international conference on computer vision (2013)

507 Citations

MMDetection: Open MMLab Detection Toolbox and Benchmark.

Kai Chen;Jiaqi Wang;Jiangmiao Pang;Yuhang Cao.
arXiv: Computer Vision and Pattern Recognition (2019)

424 Citations

DeepID-Net: Deformable deep convolutional neural networks for object detection

Wanli Ouyang;Xiaogang Wang;Xingyu Zeng;Shi Qiu.
computer vision and pattern recognition (2015)

384 Citations

Best Scientists Citing Wanli Ouyang

Xiaogang Wang

Xiaogang Wang

Chinese University of Hong Kong

Publications: 93

Huchuan Lu

Huchuan Lu

Dalian University of Technology

Publications: 89

Liang Lin

Liang Lin

Sun Yat-sen University

Publications: 70

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 68

Chunhua Shen

Chunhua Shen

University of Adelaide

Publications: 59

Wei-Shi Zheng

Wei-Shi Zheng

Sun Yat-sen University

Publications: 52

Yi Yang

Yi Yang

Zhejiang University

Publications: 49

Shaogang Gong

Shaogang Gong

Queen Mary University of London

Publications: 47

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 45

Hongsheng Li

Hongsheng Li

Chinese University of Hong Kong

Publications: 45

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 41

Chen Change Loy

Chen Change Loy

Nanyang Technological University

Publications: 40

Liang Zheng

Liang Zheng

Australian National University

Publications: 38

Shuicheng Yan

Shuicheng Yan

National University of Singapore

Publications: 38

Haibin Ling

Haibin Ling

Stony Brook University

Publications: 37

Xilin Chen

Xilin Chen

Institute Of Computing Technology

Publications: 37

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

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