Meng Wang

43.8k citations
916 papers · 28.9k · 16 hit papers · h-index 85

Impact in

    • Advanced Image and Video Retrieval Techniques
    • Image Retrieval and Classification Techniques
    • Video Surveillance and Tracking Methods
    • Multimodal Machine Learning Applications
    • Human Pose and Action Recognition
    • Video Analysis and Summarization
    • Advanced Graph Neural Networks

Papers in

    • Advanced Image and Video Retrieval Techniques 211
    • Image Retrieval and Classification Techniques 120
    • Multimodal Machine Learning Applications 112
    • Video Analysis and Summarization 103
    • Human Pose and Action Recognition 95
    • Video Surveillance and Tracking Methods 83
    • Domain Adaptation and Few-Shot Learning 78

Meng Wang

850 papers receiving 28.4k citations

Meng Wang's Hit Papers

Benchmarking Micro-Action Recognition: Dataset, Methods, and Applications 2024 · 71 citations
710+5+10Years since publication50010001.5k2.0k

Peers

Meng Wang
Comparison fields: 5 of 214
  • Computer Vision and Pattern Recognition 17.1k
  • Artificial Intelligence 10.1k
  • Information Systems 5.4k
  • Media Technology 2.0k
  • Computational Mathematics 115
Replace Tat‐Seng Chua with:
Tat‐Seng Chua Singapore
Jiebo Luo United States
C. L. Philip Chen China
Yun Fu United States
Yi Yang China
Tao Mei China
Yongdong Zhang China
Zhi‐Hua Zhou China
Quoc V. Le United States
Meng Wang relative to Tat‐Seng Chua Singapore Tat‐Seng Chua's profile →
Citations per field
00.5×1.5×2.0×
Tat‐Seng Chua · 1×
Citations per year

Countries citing papers authored by Meng Wang

Since Specialization
Citations

This map shows the geographic impact of Meng Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Meng Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meng Wang more than expected).

Fields of papers citing papers by Meng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Meng Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Meng Wang. The network helps show where Meng Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Meng Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Meng Wang Line = papers co-authored together Meng Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 916 papers — load more, or switch the sort, to bring in the rest.

#Work
1
LightGCN
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20202365
2
3-D Object Retrieval and Recognition With Hypergraph Analysis
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2012508
3
Multimodal Deep Autoencoder for Human Pose Recovery
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2015502
4
Learning to Rank Using User Clicks and Visual Features for Image Retrieval
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2014390
5
Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
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2020385
6
A Neural Influence Diffusion Model for Social Recommendation
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2019372
7
Unified Video Annotation via Multigraph Learning
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2009371
8
Multi-cue Correlation Filters for Robust Visual Tracking
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2018369
9
Adaptive Hypergraph Learning and its Application in Image Classification
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2012327
10 2009325
11
Consolidating virtual machines with dynamic bandwidth demand in data centers
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2011265
12
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
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2022264
13
Low-Light Image Enhancement With Semi-Decoupled Decomposition
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2020264
14
Generalized Incomplete Multiview Clustering With Flexible Locality Structure Diffusion
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2020242
15
DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation
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2020230
16 2019216
17 2018213
18 2012210
19 2014204
20 2012196

About Meng Wang

Meng Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Electrical and Electronic Engineering and Computational Mechanics, having authored 916 papers that have together received 28.9k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (211 papers), Image Retrieval and Classification Techniques (120 papers), Multimodal Machine Learning Applications (112 papers), Video Analysis and Summarization (103 papers), Human Pose and Action Recognition (95 papers), Video Surveillance and Tracking Methods (83 papers), Domain Adaptation and Few-Shot Learning (78 papers) and Recommender Systems and Techniques (62 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (17.1k citations), Artificial Intelligence (10.1k citations), Information Systems (5.4k citations), Media Technology (2.0k citations) and Computational Mathematics (115 citations). Meng Wang has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Richang Hong, Tat‐Seng Chua, Xiangnan He, Xian‐Sheng Hua, Zheng-Jun Zha, Dacheng Tao, Shuicheng Yan, Yongdong Zhang, Le Wu and Yan Li. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Neural Networks and Learning Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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