Lu Yuan
Impact in
- Computer Vision and Pattern Recognition top 0.05%
- Advanced Neural Network Applications
- Advanced Image Processing Techniques
- Advanced Vision and Imaging
- Image Enhancement Techniques
- Advanced Image and Video Retrieval Techniques
- Generative Adversarial Networks and Image Synthesis
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
- Media Technology top 0.1%
Papers in
-
- Advanced Image Processing Techniques 24
- Advanced Vision and Imaging 20
- Advanced Neural Network Applications 18
- Generative Adversarial Networks and Image Synthesis 18
- Multimodal Machine Learning Applications 13
- Image Enhancement Techniques 10
- Advanced Image and Video Retrieval Techniques 10
-
- Domain Adaptation and Few-Shot Learning 15
- Co-authors
- Dongdong Chen (30 shared papers)Jian Sun (14 shared papers)Yinpeng Chen (11 shared papers)Xiyang Dai (11 shared papers)Heung‐Yeung Shum (7 shared papers)Long Quan (10 shared papers)Mengchen Liu (6 shared papers)Zicheng Liu (6 shared papers)
- Journals
- ACM Transactions on Graphics (12 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)IEEE Transactions on Image Processing (2 papers)IEEE Transactions on Multimedia (2 papers)Ophthalmology and Therapy (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Lu Yuan
105 papers receiving 10.1k citations
Lu Yuan's Hit Papers
Peers
Comparison fields: 5 of 171
- Computer Vision and Pattern Recognition 8.4k
- Media Technology 1.9k
- Computer Graphics and Computer-Aided Design 727
- Artificial Intelligence 1.7k
- Industrial and Manufacturing Engineering 311
Countries citing papers authored by Lu Yuan
This map shows the geographic impact of Lu Yuan'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 Lu Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lu Yuan more than expected).
Fields of papers citing papers by Lu Yuan
This network shows the impact of papers produced by Lu Yuan. 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 Lu Yuan. The network helps show where Lu Yuan may publish in the future.
Co-authors
The 25 scholars most cited alongside Lu Yuan, 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 107 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Dynamic Convolution: Attention Over Convolution Kernels Hit paper breakdown → | 2020 | 788 |
| 2 | Image deblurring with blurred/noisy image pairs Hit paper breakdown → | 2007 | 573 |
| 3 | Dynamic Head: Unifying Object Detection Heads with Attentions Hit paper breakdown → | 2021 | 551 |
| 4 | Gated Context Aggregation Network for Image Dehazing and Deraining Hit paper breakdown → | 2019 | 518 |
| 5 | Rethinking Classification and Localization for Object Detection Hit paper breakdown → | 2020 | 491 |
| 6 | Deep Feature Flow for Video Recognition Hit paper breakdown → | 2017 | 416 |
| 7 | Flow-Guided Feature Aggregation for Video Object Detection Hit paper breakdown → | 2017 | 413 |
| 8 | Mobile-Former: Bridging MobileNet and Transformer Hit paper breakdown → | 2022 | 411 |
| 9 | Image completion with structure propagation Hit paper breakdown → | 2005 | 370 |
| 10 | Vector Quantized Diffusion Model for Text-to-Image Synthesis Hit paper breakdown → | 2022 | 355 |
| 11 | 2017 | 303 | |
| 12 | RegionCLIP: Region-based Language-Image Pretraining Hit paper breakdown → | 2022 | 276 |
| 13 | Lite-HRNet: A Lightweight High-Resolution Network Hit paper breakdown → | 2021 | 264 |
| 14 | Dynamic DETR: End-to-End Object Detection with Dynamic Attention Hit paper breakdown → | 2021 | 257 |
| 15 | 2013 | 236 | |
| 16 | 2007 | 220 | |
| 17 | 2006 | 205 | |
| 18 | An Empirical Study of Training End-to-End Vision-and-Language Transformers Hit paper breakdown → | 2022 | 204 |
| 19 | Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding Hit paper breakdown → | 2021 | 204 |
| 20 | 2018 | 188 |
About Lu Yuan
Lu Yuan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Computer Graphics and Computer-Aided Design and Radiology, Nuclear Medicine and Imaging, having authored 107 papers that have together received 10.4k indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (24 papers), Advanced Vision and Imaging (20 papers), Advanced Neural Network Applications (18 papers), Generative Adversarial Networks and Image Synthesis (18 papers), Domain Adaptation and Few-Shot Learning (15 papers), Multimodal Machine Learning Applications (13 papers), Image Enhancement Techniques (10 papers) and Advanced Image and Video Retrieval Techniques (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (8.4k citations), Media Technology (1.9k citations), Computer Graphics and Computer-Aided Design (727 citations), Artificial Intelligence (1.7k citations) and Industrial and Manufacturing Engineering (311 citations). Lu Yuan has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Dongdong Chen, Jian Sun, Yinpeng Chen, Xiyang Dai, Heung‐Yeung Shum, Long Quan, Mengchen Liu, Zicheng Liu, Jing Liao and Gang Hua. Their work appears in journals such as ACM Transactions on Graphics, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Multimedia and Ophthalmology and Therapy.
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.