Deng-Ping Fan
Impact in
- Computer Vision and Pattern Recognition top 0.02%
- Visual Attention and Saliency Detection
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Image Enhancement Techniques
- Video Surveillance and Tracking Methods
- Media Technology top 0.05%
- Advanced Image Fusion Techniques
Papers in
-
- Visual Attention and Saliency Detection 51
- Advanced Image and Video Retrieval Techniques 34
- Advanced Neural Network Applications 22
- Image Enhancement Techniques 19
- Image and Video Quality Assessment 10
- Medical Image Segmentation Techniques 7
- Multimodal Machine Learning Applications 6
- Co-authors
- Ling Shao (21 shared papers)Ming‐Ming Cheng (20 shared papers)Ge-Peng Ji (22 shared papers)Wenhai Wang (3 shared papers)Xiang Li (3 shared papers)Kaitao Song (2 shared papers)Enze Xie (2 shared papers)Tong Lü (2 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (12 papers)Computational Visual Media (6 papers)Expert Systems with Applications (2 papers)Science China Information Sciences (2 papers)International Journal of Computer Vision (2 papers)
- Partner nations
- ChinaUnited Arab EmiratesSwitzerland
In The Last Decade
Deng-Ping Fan
90 papers receiving 16.7k citations
Deng-Ping Fan's Hit Papers
Peers
Comparison fields: 5 of 167
- Computer Vision and Pattern Recognition 13.0k
- Media Technology 2.3k
- Sensory Systems 1.0k
- Human-Computer Interaction 675
- Radiology, Nuclear Medicine and Imaging 1.9k
Countries citing papers authored by Deng-Ping Fan
This map shows the geographic impact of Deng-Ping Fan'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 Deng-Ping Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deng-Ping Fan more than expected).
Fields of papers citing papers by Deng-Ping Fan
This network shows the impact of papers produced by Deng-Ping Fan. 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 Deng-Ping Fan. The network helps show where Deng-Ping Fan may publish in the future.
Co-authors
The 25 scholars most cited alongside Deng-Ping Fan, 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 91 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions Hit paper breakdown → | 2021 | 3383 |
| 2 | PVT v2: Improved baselines with pyramid vision transformer Hit paper breakdown → | 2022 | 1450 |
| 3 | Structure-Measure: A New Way to Evaluate Foreground Maps Hit paper breakdown → | 2017 | 1331 |
| 4 | EGNet: Edge Guidance Network for Salient Object Detection Hit paper breakdown → | 2019 | 924 |
| 5 | Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images Hit paper breakdown → | 2020 | 891 |
| 6 | PraNet: Parallel Reverse Attention Network for Polyp Segmentation Hit paper breakdown → | 2020 | 845 |
| 7 | Camouflaged Object Detection Hit paper breakdown → | 2020 | 542 |
| 8 | Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks Hit paper breakdown → | 2020 | 518 |
| 9 | Concealed Object Detection Hit paper breakdown → | 2021 | 457 |
| 10 | Shifting More Attention to Video Salient Object Detection Hit paper breakdown → | 2019 | 412 |
| 11 | Camouflaged Object Segmentation with Distraction Mining Hit paper breakdown → | 2021 | 352 |
| 12 | Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection Hit paper breakdown → | 2019 | 338 |
| 13 | Simultaneously Localize, Segment and Rank the Camouflaged Objects Hit paper breakdown → | 2021 | 319 |
| 14 | UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders Hit paper breakdown → | 2020 | 298 |
| 15 | Salient Object Detection via Integrity Learning Hit paper breakdown → | 2022 | 276 |
| 16 | 2018 | 276 | |
| 17 | Segment anything model for medical images? Hit paper breakdown → | 2023 | 275 |
| 18 | JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection Hit paper breakdown → | 2020 | 267 |
| 19 | BBS-Net: RGB-D Salient Object Detection with a Bifurcated Backbone Strategy Network Hit paper breakdown → | 2020 | 258 |
| 20 | Mutual Graph Learning for Camouflaged Object Detection Hit paper breakdown → | 2021 | 241 |
About Deng-Ping Fan
Deng-Ping Fan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Human-Computer Interaction, having authored 91 papers that have together received 16.9k indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (51 papers), Advanced Image and Video Retrieval Techniques (34 papers), Advanced Neural Network Applications (22 papers), Image Enhancement Techniques (19 papers), Image and Video Quality Assessment (10 papers), Face Recognition and Perception (9 papers), Medical Image Segmentation Techniques (7 papers) and Multimodal Machine Learning Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (13.0k citations), Media Technology (2.3k citations), Sensory Systems (1.0k citations), Human-Computer Interaction (675 citations) and Radiology, Nuclear Medicine and Imaging (1.9k citations). Deng-Ping Fan has collaborated with scholars based in China, United Arab Emirates and Switzerland. Frequent co-authors include Ling Shao, Ming‐Ming Cheng, Ge-Peng Ji, Wenhai Wang, Xiang Li, Kaitao Song, Enze Xie, Tong Lü, Ding Liang and Ping Luo. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Computational Visual Media, Expert Systems with Applications, Science China Information Sciences and International Journal of Computer Vision.
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.