Buyu Liu
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- Advanced Vision and Imaging 7
- Human Pose and Action Recognition 4
- Multimodal Machine Learning Applications 4
- Advanced Neural Network Applications 3
- Visual Attention and Saliency Detection 2
- Human-Computer Interaction top 10%
- Gaze Tracking and Assistive Technology 2
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- Domain Adaptation and Few-Shot Learning 3
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- Remote Sensing and LiDAR Applications 2
- Co-authors
- Vittorio FerrariXuming HeSamuel SchulterManmohan ChandrakerBingbing ZhuangJun YuJun BaoZiyan Wang
- Journals
- IEEE Transactions on Image Processing (1 paper)IEEE Transactions on Circuits and Systems for Video Technology (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (3 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Buyu Liu
16 papers receiving 235 citations
Peers
Comparison fields: 5 of 55
- Computer Vision and Pattern Recognition 185
- Human-Computer Interaction 34
- Artificial Intelligence 67
- Geology 10
- Aerospace Engineering 39
Countries citing papers authored by Buyu Liu
This map shows the geographic impact of Buyu Liu'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 Buyu Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Buyu Liu more than expected).
Fields of papers citing papers by Buyu Liu
This network shows the impact of papers produced by Buyu Liu. 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 Buyu Liu. The network helps show where Buyu Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Buyu Liu, 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 | 2024 | 3 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 17 | |
| 7 | 2022 | 17 | |
| 8 | 2022 | 16 | |
| 9 | 2022 | 34 | |
| 10 | 2022 | 4 | |
| 11 | 2020 | 12 | |
| 12 | 2020 | 13 | |
| 13 | 2019 | 24 | |
| 14 | 2019 | 5 | |
| 15 | 2017 | 43 | |
| 16 | 2015 | 10 | |
| 17 | 2015 | 33 | |
| 18 | 2014 | 4 |
About Buyu Liu
Buyu Liu is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Geology, having authored 18 papers that have together received 244 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (7 papers), Human Pose and Action Recognition (4 papers), Multimodal Machine Learning Applications (4 papers), Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Gaze Tracking and Assistive Technology (2 papers), Visual Attention and Saliency Detection (2 papers) and Remote Sensing and LiDAR Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (185 citations), Human-Computer Interaction (34 citations) and Artificial Intelligence (67 citations). Buyu Liu has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Vittorio Ferrari, Xuming He, Samuel Schulter, Manmohan Chandraker, Bingbing Zhuang, Jun Yu, Jun Bao, Ziyan Wang, Stephen Jay Gould and Inkyu Shin. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.