Ping Luo
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Neural Network Applications 64
- Advanced Image and Video Retrieval Techniques 36
- Generative Adversarial Networks and Image Synthesis 30
- Face recognition and analysis 25
- Multimodal Machine Learning Applications 23
- Video Surveillance and Tracking Methods 20
- Human Pose and Action Recognition 19
- Media Technology top 0.1%
- Artificial Intelligence top 0.1%
- Domain Adaptation and Few-Shot Learning 43
- Signal Processing top 0.2%
Ping Luo
222 papers receiving 21.0k citations
Hit Papers
Peers
Comparison fields: 5 of 213
- Computer Vision and Pattern Recognition 15.8k
- Media Technology 1.8k
- Artificial Intelligence 5.0k
- Computer Graphics and Computer-Aided Design 527
- Signal Processing 1.4k
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-authorship network
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 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 11 | |
| 6 | 2024 | 5 | |
| 7 | 2024 | 13 | |
| 8 | 2023 | 47 | |
| 9 | 2023 | 4 | |
| 10 | 2023 | 5 | |
| 11 | 2023 | 61 | |
| 12 | 2022 | 66 | |
| 13 | 2022 | 33 | |
| 14 | 2021 | 4 | |
| 15 | 2021 | 0 | |
| 16 | Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning | 2021 | 8 |
| 17 | Research Status and Outlook of PD-1/PD-L1 Inhibitors for Cancer Therapy | 2020 | 3 |
| 18 | A novel mutation panel for predicting etoposide resistance in small-cell lung cancer | 2019 | 4 |
| 19 | 2019 | 31 | |
| 20 | Differentiable Dynamic Normalization for Learning Deep Representation | 2019 | 11 |
About Ping Luo
Ping Luo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases, having authored 237 papers that have together received 21.6k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (64 papers), Domain Adaptation and Few-Shot Learning (43 papers), Advanced Image and Video Retrieval Techniques (36 papers), Generative Adversarial Networks and Image Synthesis (30 papers), Face recognition and analysis (25 papers), Multimodal Machine Learning Applications (23 papers), Video Surveillance and Tracking Methods (20 papers) and Human Pose and Action Recognition (19 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (15.8k citations), Media Technology (1.8k citations) and Artificial Intelligence (5.0k citations). Ping Luo has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Xiaoou Tang, Xiaogang Wang, Ziwei Liu, Enze Xie, Wenhai Wang, Ding Liang, Tong Lü, Ling Shao, Deng-Ping Fan and Kaitao Song. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, IEEE Transactions on Image Processing, Vaccine and Cell Death and Disease.
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.