Yonglong Tian

8.9k citations
24 papers · 1.9k indexed · 2 hit papers · h-index 13

Yonglong Tian

21 papers receiving 1.8k citations

Hit Papers

Through-Wall Human Pose Estimation Using Radio Signals4472015202620182022100200300400

Peers

Yonglong Tian
Comparison fields: 5 of 105
  • Computer Vision and Pattern Recognition 1.1k
  • Human-Computer Interaction 192
  • Artificial Intelligence 498
  • Instrumentation 40
  • Signal Processing 122
Replace Du Q. Huynh with:
Du Q. Huynh Australia
Esther Koller-Meier Switzerland
Hassan Foroosh United States
Dima Damen United Kingdom
Linga Reddy Cenkeramaddi Norway
John Zelek Canada
Yuexin Ma China
Kai‐Tai Song Taiwan
Siyu Tang Germany
Yonglong Tian relative to Du Q. Huynh Australia Du Q. Huynh's profile →
Citations per field
00.5×1.5×1.8×
Du Q. Huynh · 1×
Citations per year

Countries citing papers authored by Yonglong Tian

Since Specialization
Citations

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

Fields of papers citing papers by Yonglong Tian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20252
3 20250
4 20242
5 20245
6 202410
7 20240
8 20235
9 202233
10 202120
11 202112
12
What Makes for Good Views for Contrastive Learning
202049
13 20208
14
Probgan: Towards probabilistic GaN with theoretical guarantees
201913
15
Learning to Infer and Execute 3D Shape Programs
201915
16
Representation Learning on Graphs with Jumping Knowledge Networks
2018131
17 2018131
18 2018283
19 2016132
20
Deep Learning Strong Parts for Pedestrian Detectionbreakdown →
2015376

About Yonglong Tian

Yonglong Tian is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 24 papers that have together received 1.9k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (6 papers), Advanced Neural Network Applications (5 papers), Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (4 papers), Video Surveillance and Tracking Methods (3 papers), Anomaly Detection Techniques and Applications (2 papers), Hand Gesture Recognition Systems (2 papers) and Fiber-reinforced polymer composites (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Human-Computer Interaction (192 citations) and Artificial Intelligence (498 citations). Yonglong Tian has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Xiaoou Tang, Xiaogang Wang, Ping Luo, Dina Katabi, Hang Zhao, Tianhong Li, Mohammad Abu Alsheikh, Antonio Torralba, M. Zhao and Zachary Kabelac. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Chemical Engineering Journal and Journal of Applied Polymer Science.

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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