Junnan Li

4.0k citations
18 papers · 462 · h-index 10

Impact in

    • Multimodal Machine Learning Applications
    • Human Pose and Action Recognition
    • Advanced Image and Video Retrieval Techniques
    • Video Analysis and Summarization
    • Advanced Neural Network Applications
    • Video Surveillance and Tracking Methods
    • Domain Adaptation and Few-Shot Learning
    • Anomaly Detection Techniques and Applications

Papers in

Junnan Li

17 papers receiving 452 citations

Peers

Junnan Li
Comparison fields: 5 of 57
  • Computer Vision and Pattern Recognition 367
  • Artificial Intelligence 194
  • Human-Computer Interaction 18
  • Computer Science Applications 11
  • Health Informatics 2
Replace Sandra Ebert with:
Sandra Ebert Germany
Diego Tosato Italy
Sicong Liu China
Alper Aydemir Sweden
Shunzhi Yang China
Baoxiong Jia China
Sarvesh Vishwakarma India
Pengfei Xu China
Qiushan Guo China
Kazuaki Nakamura Japan
Junnan Li relative to Sandra Ebert Germany Sandra Ebert's profile →
Citations per field
00.5×20×40×58×
Sandra Ebert · 1×
Citations per year

Countries citing papers authored by Junnan Li

Since Specialization
Citations

This map shows the geographic impact of Junnan Li'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 Junnan Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junnan Li more than expected).

Fields of papers citing papers by Junnan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Junnan Li. 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 Junnan Li. The network helps show where Junnan Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Junnan Li, 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 Junnan Li Line = papers co-authored together Junnan Li links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201992
2 201983
3 202364
4 201752
5 202241
6 201929
7 201729
8 201727
9 201614
10 20199
11 20198
12 20195
13 20204
14 20202
15
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
20211
16 20191
17 20171
18 20240

About Junnan Li

Junnan Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Information Systems and Hardware and Architecture, having authored 18 papers that have together received 462 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (8 papers), Domain Adaptation and Few-Shot Learning (6 papers), Video Analysis and Summarization (5 papers), Human Pose and Action Recognition (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Software-Defined Networks and 5G (4 papers), Cloud Computing and Resource Management (2 papers) and Speech and dialogue systems (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (367 citations), Artificial Intelligence (194 citations), Human-Computer Interaction (18 citations), Computer Science Applications (11 citations) and Health Informatics (2 citations). Junnan Li has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include Mohan Kankanhalli, Yongkang Wong, Qi Zhao, Steven C. H. Hoi, Anthony Meng Huat Tiong, Boyang Li, Yuting Su, An-An Liu, Dongxu Li and Jiaxian Guo. Their work appears in journals such as IEEE Transactions on Multimedia, Multimedia Tools and Applications, ACM Transactions on Multimedia Computing Communications and Applications, IEEE Network and Computer Vision and Image Understanding.

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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