Zhuowen Tu
- Computer Vision and Pattern Recognition top 0.02%
- Advanced Image and Video Retrieval Techniques 57
- Image Retrieval and Classification Techniques 32
- Medical Image Segmentation Techniques 29
- Advanced Neural Network Applications 28
- Multimodal Machine Learning Applications 15
- Generative Adversarial Networks and Image Synthesis 13
- Face and Expression Recognition 12
- Media Technology top 0.05%
- Artificial Intelligence top 0.1%
- Domain Adaptation and Few-Shot Learning 20
- Neurology top 1%
- Journals
- Journal of Neuroscience (1 paper)PLoS ONE (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (8 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Zhuowen Tu
163 papers receiving 20.4k citations
Hit Papers
Peers
Comparison fields: 5 of 215
- Computer Vision and Pattern Recognition 14.1k
- Media Technology 2.2k
- Artificial Intelligence 5.3k
- Neurology 831
- Radiology, Nuclear Medicine and Imaging 2.1k
Countries citing papers authored by Zhuowen Tu
This map shows the geographic impact of Zhuowen Tu'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 Zhuowen Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhuowen Tu more than expected).
Fields of papers citing papers by Zhuowen Tu
This network shows the impact of papers produced by Zhuowen Tu. 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 Zhuowen Tu. The network helps show where Zhuowen Tu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Zhuowen Tu, 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 | 2023 | 18 | |
| 4 | 2022 | 11 | |
| 5 | MeMOT: Multi-Object Tracking with Memorybreakdown → | 2022 | 123 |
| 6 | 2021 | 28 | |
| 7 | Attentional Constellation Nets for Few-Shot Learning. | 2020 | 22 |
| 8 | Geometry-Aware End-to-End Skeleton Detection. | 2019 | 5 |
| 9 | Deeply Supervised Salient Object Detection with Short Connectionsbreakdown → | 2018 | 497 |
| 10 | Introspective Classifier Learning: Empower Generatively. | 2017 | 1 |
| 11 | Aggregated Residual Transformations for Deep Neural Networksbreakdown → | 2017 | 7181 |
| 12 | Introspective Classification with Convolutional Nets | 2017 | 9 |
| 13 | On the Connection of Deep Fusion to Ensembling. | 2016 | 23 |
| 14 | Learning to predict from crowdsourced data | 2014 | 31 |
| 15 | Similarity network fusion for aggregating data types on a genomic scalebreakdown → | 2014 | 1267 |
| 16 | Max-Margin Multiple-Instance Dictionary Learning | 2013 | 78 |
| 17 | 2009 | 156 | |
| 18 | 2005 | 312 | |
| 19 | A FRAMEWORK FOR AUTOMATIC RECOGNITION OF SPATIAL FEATURES FROM MOBILE MAPPING IMAGERY | 2002 | 4 |
| 20 | 2002 | 405 |
About Zhuowen Tu
Zhuowen Tu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mathematics, having authored 167 papers that have together received 21.0k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (57 papers), Image Retrieval and Classification Techniques (32 papers), Medical Image Segmentation Techniques (29 papers), Advanced Neural Network Applications (28 papers), Domain Adaptation and Few-Shot Learning (20 papers), Multimodal Machine Learning Applications (15 papers), Generative Adversarial Networks and Image Synthesis (13 papers) and Face and Expression Recognition (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (14.1k citations), Media Technology (2.2k citations) and Artificial Intelligence (5.3k citations). Zhuowen Tu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Saining Xie, Piotr Dollár, Kaiming He, Ross Girshick, Xiang Bai, Serge Belongie, Bo Wang, Alan Yuille, Wenyu Liu and Song-Chun Zhu. Their work appears in journals such as Journal of Neuroscience, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.