Ziwei Liu
- Computer Vision and Pattern Recognition top 0.02%
- Generative Adversarial Networks and Image Synthesis 45
- Human Pose and Action Recognition 34
- Advanced Vision and Imaging 34
- Advanced Neural Network Applications 30
- Multimodal Machine Learning Applications 25
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- Computer Graphics and Visualization Techniques 22
- Geology top 0.05%
- Computational Mechanics top 0.1%
- 3D Shape Modeling and Analysis 29
- Artificial Intelligence top 0.1%
- Domain Adaptation and Few-Shot Learning 30
Ziwei Liu
204 papers receiving 18.9k citations
Hit Papers
Peers
Comparison fields: 5 of 201
- Computer Vision and Pattern Recognition 12.5k
- Computer Graphics and Computer-Aided Design 1.5k
- Geology 2.0k
- Computational Mechanics 3.6k
- Artificial Intelligence 5.0k
Countries citing papers authored by Ziwei Liu
This map shows the geographic impact of Ziwei 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 Ziwei Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ziwei Liu more than expected).
Fields of papers citing papers by Ziwei Liu
This network shows the impact of papers produced by Ziwei 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 Ziwei Liu. The network helps show where Ziwei Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ziwei 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 3 | |
| 4 | 2024 | 12 | |
| 5 | 2024 | 6 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 8 | |
| 8 | Class-Incremental Learning: A Surveybreakdown → | 2024 | 58 |
| 9 | 2024 | 2 | |
| 10 | MotionDiffuse: Text-Driven Human Motion Generation With Diffusion Modelbreakdown → | 2024 | 83 |
| 11 | 2023 | 21 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 36 | |
| 14 | 2023 | 2 | |
| 15 | 2023 | 2 | |
| 16 | Conditional Prompt Learning for Vision-Language Modelsbreakdown → | 2022 | 742 |
| 17 | 2022 | 11 | |
| 18 | Long Non-Coding RNA LEF1-AS1 Promotes Migration, Invasion and Metastasis of Colon Cancer Cells Through miR-30-5p/SOX9 Axis | 2020 | 1 |
| 19 | 2020 | 70 | |
| 20 | 2020 | 2 |
About Ziwei Liu
Ziwei Liu is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 222 papers that have together received 19.4k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (45 papers), Human Pose and Action Recognition (34 papers), Advanced Vision and Imaging (34 papers), Domain Adaptation and Few-Shot Learning (30 papers), Advanced Neural Network Applications (30 papers), 3D Shape Modeling and Analysis (29 papers), Multimodal Machine Learning Applications (25 papers) and Computer Graphics and Visualization Techniques (22 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (12.5k citations), Computer Graphics and Computer-Aided Design (1.5k citations) and Geology (2.0k citations). Ziwei Liu has collaborated with scholars based in Singapore, China and Hong Kong. Frequent co-authors include Ping Luo, Xiaoou Tang, Xiaogang Wang, Chen Change Loy, Kaiyang Zhou, Yongbin Sun, Yue Wang, Sanjay E. Sarma, Justin Solomon and Michael M. Bronstein. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, ACM Transactions on Graphics, Macromolecules and Pattern Recognition.
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.