Bolei Zhou
Impact in
- Computer Vision and Pattern Recognition top 0.02%
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Generative Adversarial Networks and Image Synthesis
- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Artificial Intelligence top 0.05%
- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
Papers in
-
- Advanced Image and Video Retrieval Techniques 18
- Advanced Neural Network Applications 17
- Generative Adversarial Networks and Image Synthesis 17
- Human Pose and Action Recognition 12
- Video Surveillance and Tracking Methods 11
- Advanced Vision and Imaging 11
- Multimodal Machine Learning Applications 11
-
- Anomaly Detection Techniques and Applications 10
- Co-authors
- Antonio Torralba (13 shared papers)Aude Oliva (8 shared papers)Àgata Lapedriza (6 shared papers)Aditya Khosla (3 shared papers)Hang Zhao (3 shared papers)Xavier Puig (3 shared papers)Sanja Fidler (3 shared papers)Yujun Shen (13 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (7 papers)IEEE Robotics and Automation Letters (5 papers)International Journal of Computer Vision (4 papers)Journal of Vision (2 papers)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- Hong KongUnited StatesChina
In The Last Decade
Bolei Zhou
76 papers receiving 18.9k citations
Bolei Zhou's Hit Papers
Peers
Comparison fields: 5 of 204
- Computer Vision and Pattern Recognition 12.4k
- Artificial Intelligence 7.1k
- Health Informatics 238
- Computer Graphics and Computer-Aided Design 486
- Media Technology 1.2k
Countries citing papers authored by Bolei Zhou
This map shows the geographic impact of Bolei Zhou'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 Bolei Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bolei Zhou more than expected).
Fields of papers citing papers by Bolei Zhou
This network shows the impact of papers produced by Bolei Zhou. 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 Bolei Zhou. The network helps show where Bolei Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Bolei Zhou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Learning Deep Features for Discriminative Localization Hit paper breakdown → | 2016 | 6518 |
| 2 | Places: A 10 Million Image Database for Scene Recognition Hit paper breakdown → | 2017 | 2321 |
| 3 | Scene Parsing through ADE20K Dataset Hit paper breakdown → | 2017 | 1767 |
| 4 | Learning Deep Features for Scene Recognition using Places Database Hit paper breakdown → | 2014 | 1556 |
| 5 | Semantic Understanding of Scenes Through the ADE20K Dataset Hit paper breakdown → | 2018 | 975 |
| 6 | Interpreting the Latent Space of GANs for Semantic Face Editing Hit paper breakdown → | 2020 | 562 |
| 7 | Measuring human perceptions of a large-scale urban region using machine learning Hit paper breakdown → | 2018 | 514 |
| 8 | 2017 | 314 | |
| 9 | Closed-Form Factorization of Latent Semantics in GANs Hit paper breakdown → | 2021 | 295 |
| 10 | Multimodal Motion Prediction with Stacked Transformers Hit paper breakdown → | 2021 | 295 |
| 11 | Temporal Pyramid Network for Action Recognition Hit paper breakdown → | 2020 | 279 |
| 12 | Object Detectors Emerge in Deep Scene CNNs | 2015 | 275 |
| 13 | 2012 | 225 | |
| 14 | 2017 | 219 | |
| 15 | 2020 | 207 | |
| 16 | 2020 | 182 | |
| 17 | 2020 | 170 | |
| 18 | 2018 | 165 | |
| 19 | 2019 | 146 | |
| 20 | 2020 | 143 |
About Bolei Zhou
Bolei Zhou is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Control and Systems Engineering and Ocean Engineering, having authored 85 papers that have together received 19.4k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (18 papers), Advanced Neural Network Applications (17 papers), Generative Adversarial Networks and Image Synthesis (17 papers), Human Pose and Action Recognition (12 papers), Video Surveillance and Tracking Methods (11 papers), Advanced Vision and Imaging (11 papers), Multimodal Machine Learning Applications (11 papers) and Anomaly Detection Techniques and Applications (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (12.4k citations), Artificial Intelligence (7.1k citations), Health Informatics (238 citations), Computer Graphics and Computer-Aided Design (486 citations) and Media Technology (1.2k citations). Bolei Zhou has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Antonio Torralba, Aude Oliva, Àgata Lapedriza, Aditya Khosla, Hang Zhao, Xavier Puig, Sanja Fidler, Yujun Shen, Jianxiong Xiao and Xiaoou Tang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Robotics and Automation Letters, International Journal of Computer Vision, Journal of Vision and Proceedings of the National Academy of Sciences.
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.