Ping Luo
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Video Analysis and Summarization
- Human Pose and Action Recognition
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- Topic Modeling
- Natural Language Processing Techniques
Papers in
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- Generative Adversarial Networks and Image Synthesis 3
- Human Pose and Action Recognition 2
- Advanced Image and Video Retrieval Techniques 2
- Multimodal Machine Learning Applications 2
- Digital Imaging for Blood Diseases 1
- Co-authors
- Lewei Lu (1 shared paper)Sen Xing (1 shared paper)Tong Lü (1 shared paper)Yifeng Dai (1 shared paper)Qinglong Zhang (1 shared paper)Wenhai Wang (1 shared paper)Guo Chen (1 shared paper)Bin Li (1 shared paper)
In The Last Decade
Ping Luo
11 papers receiving 263 citations
Ping Luo's Hit Papers
Peers
Comparison fields: 5 of 58
- Computer Vision and Pattern Recognition 123
- Artificial Intelligence 85
- Automotive Engineering 25
- Computer Graphics and Computer-Aided Design 6
- Signal Processing 17
Countries citing papers authored by Ping Luo
This map shows the geographic impact of Ping Luo'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 Ping Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ping Luo more than expected).
Fields of papers citing papers by Ping Luo
This network shows the impact of papers produced by Ping Luo. 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 Ping Luo. The network helps show where Ping Luo may publish in the future.
Co-authors
The 25 scholars most cited alongside Ping Luo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Intern VL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks Hit paper breakdown → | 2024 | 163 |
| 2 | DriveLM: Driving with Graph Visual Question Answering Hit paper breakdown → | 2024 | 75 |
| 3 | 2020 | 7 | |
| 4 | 2024 | 7 | |
| 5 | 2021 | 7 | |
| 6 | 2024 | 5 | |
| 7 | 2024 | 3 | |
| 8 | 2022 | 1 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 1 | |
| 11 | 2012 | 1 | |
| 12 | 2025 | 0 | |
| 13 | 2024 | 0 |
About Ping Luo
Ping Luo is a scholar working on Computer Vision and Pattern Recognition, Information Systems, Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 13 papers that have together received 271 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (3 papers), Human Pose and Action Recognition (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Advanced Malware Detection Techniques (2 papers), Multimodal Machine Learning Applications (2 papers), Network Security and Intrusion Detection (1 paper), Digital Imaging for Blood Diseases (1 paper) and Immunotherapy and Immune Responses (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (123 citations), Artificial Intelligence (85 citations), Automotive Engineering (25 citations), Computer Graphics and Computer-Aided Design (6 citations) and Signal Processing (17 citations). Ping Luo has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Lewei Lu, Sen Xing, Tong Lü, Yifeng Dai, Qinglong Zhang, Wenhai Wang, Guo Chen, Bin Li, Jiannan Wu and Xizhou Zhu. Their work appears in journals such as International Journal of Computer Vision, Biomedical Optics Express, Electronics, BMJ Open and International Journal of Information and Computer Security.
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.