Radu Timofte

38.8k total citations · 20 hit papers
180 papers, 15.0k citations indexed

About

Radu Timofte is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Radu Timofte has authored 180 papers receiving a total of 15.0k indexed citations (citations by other indexed papers that have themselves been cited), including 162 papers in Computer Vision and Pattern Recognition, 45 papers in Media Technology and 19 papers in Artificial Intelligence. Recurrent topics in Radu Timofte's work include Advanced Image Processing Techniques (78 papers), Advanced Vision and Imaging (51 papers) and Image and Signal Denoising Methods (39 papers). Radu Timofte is often cited by papers focused on Advanced Image Processing Techniques (78 papers), Advanced Vision and Imaging (51 papers) and Image and Signal Denoising Methods (39 papers). Radu Timofte collaborates with scholars based in Switzerland, Belgium and Germany. Radu Timofte's co-authors include Luc Van Gool, Eirikur Agustsson, Kai Zhang, Jingyun Liang, Jiezhang Cao, Rasmus Rothe, Guolei Sun, Yulun Zhang, Martin Danelljan and Markus Mathias and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Radu Timofte

171 papers receiving 14.6k citations

Hit Papers

SwinIR: Image Restoration Usin... 2012 2026 2016 2021 2021 2017 2013 2022 2018 500 1000 1.5k 2.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. SwinIR: Image Restoration Using Swin Transformer
    2021 2.4k citations Jingyun Liang, Jiezhang Cao et al. profile →
  2. NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study
    2017 2.3k citations Eirikur Agustsson, Radu Timofte profile →
  3. Anchored Neighborhood Regression for Fast Example-Based Super-Resolution
    2013 960 citations Radu Timofte, Luc Van Gool et al. Lirias (KU Leuven) profile →
  4. RePaint: Inpainting using Denoising Diffusion Probabilistic Models
    2022 797 citations Martin Danelljan, Radu Timofte et al. profile →
  5. O-HAZE: A Dehazing Benchmark with Real Hazy and Haze-Free Outdoor Images
    2018 505 citations Radu Timofte et al. profile →
  6. Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks
    2016 502 citations Radu Timofte, Luc Van Gool et al. profile →
  7. DEX: Deep EXpectation of Apparent Age from a Single Image
    2015 402 citations Radu Timofte, Luc Van Gool et al. profile →
  8. CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion
    2023 394 citations Yulun Zhang, Radu Timofte et al. profile →
  9. Pedestrian detection at 100 frames per second
    2012 360 citations R.E. Benenson, Markus Mathias et al. Lirias (KU Leuven) profile →
  10. DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks
    2017 354 citations Radu Timofte et al. Lirias (KU Leuven) profile →
  11. Seven Ways to Improve Example-Based Single Image Super Resolution
    2016 288 citations Radu Timofte, Luc Van Gool et al. Lirias (KU Leuven) profile →
  12. Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement
    2023 281 citations Yuanhao Cai, Hao Bian et al. profile →
  13. Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction
    2022 212 citations Yuanhao Cai, Haoqian Wang et al. profile →
  14. MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction
    2022 172 citations Yuanhao Cai, Haoqian Wang et al. profile →
  15. DDFM: Denoising Diffusion Model for Multi-Modality Image Fusion
    2023 163 citations Yulun Zhang, Radu Timofte et al. profile →
  16. Efficient and Explicit Modelling of Image Hierarchies for Image Restoration
    2023 143 citations Yawei Li, Radu Timofte et al. profile →
  17. Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis
    2023 106 citations Kai Zhang, Yawei Li et al. arXiv (Cornell University) profile →
  18. Denoising Diffusion Models for Plug-and-Play Image Restoration
    2023 83 citations Kai Zhang, Jingyun Liang et al. profile →
  19. VRT: A Video Restoration Transformer
    2024 76 citations Jingyun Liang, Jiezhang Cao et al. profile →
  20. Equivariant Multi-Modality Image Fusion
    2024 65 citations Yulun Zhang, Radu Timofte et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Radu Timofte Switzerland 45 12.5k 5.8k 1.1k 804 769 180 15.0k
Johannes Totz United Kingdom 9 10.4k 0.8× 4.8k 0.8× 925 0.8× 730 0.9× 446 0.6× 12 12.5k
Kyoung Mu Lee South Korea 43 11.3k 0.9× 4.3k 0.7× 871 0.8× 545 0.7× 454 0.6× 194 12.7k
Zehan Wang China 12 10.4k 0.8× 4.8k 0.8× 996 0.9× 725 0.9× 461 0.6× 49 12.8k
Ferenc Huszár United Kingdom 12 10.0k 0.8× 4.7k 0.8× 1.2k 1.1× 656 0.8× 469 0.6× 18 12.4k
Wenzhe Shi United Kingdom 24 11.1k 0.9× 5.0k 0.9× 1.2k 1.0× 916 1.1× 536 0.7× 61 14.1k
Guangtao Zhai China 59 11.3k 0.9× 5.1k 0.9× 675 0.6× 814 1.0× 827 1.1× 579 14.8k
Andrew P. Aitken United Kingdom 9 10.2k 0.8× 4.8k 0.8× 924 0.8× 680 0.8× 446 0.6× 11 12.6k
Weisi Lin Singapore 82 19.4k 1.6× 7.3k 1.3× 1.0k 0.9× 658 0.8× 2.0k 2.6× 612 22.4k
José Caballero United Kingdom 11 10.9k 0.9× 5.0k 0.9× 1.1k 1.0× 1.1k 1.4× 477 0.6× 14 14.3k

Countries citing papers authored by Radu Timofte

Since Specialization
Citations

This map shows the geographic impact of Radu Timofte'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 Radu Timofte with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Radu Timofte more than expected).

Fields of papers citing papers by Radu Timofte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Radu Timofte. 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 Radu Timofte. The network helps show where Radu Timofte may publish in the future.

Co-authorship network of co-authors of Radu Timofte

This figure shows the co-authorship network connecting the top 25 collaborators of Radu Timofte. A scholar is included among the top collaborators of Radu Timofte based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Radu Timofte. Radu Timofte is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Le, et al.. (2025). SF‐YOLO: A Novel YOLO Framework for Small Object Detection in Aerial Scenes. IET Image Processing. 19(1). 1 indexed citations
2.
Jiang, Qiuping, et al.. (2024). High-Precision Dichotomous Image Segmentation With Frequency and Scale Awareness. IEEE Transactions on Neural Networks and Learning Systems. 36(5). 8619–8631. 5 indexed citations
3.
Dharejo, Fayaz Ali, Iyyakutti Iyappan Ganapathi, Le Wang, et al.. (2024). Multi-Distillation Underwater Image Super-Resolution via Wavelet Transform. IEEE Access. 12. 131083–131099. 1 indexed citations
4.
Timofte, Radu, et al.. (2024). Scoring facial attractiveness with deep convolutional neural networks: How training on standardized images reduces the bias of facial expressions. Orthodontics and Craniofacial Research. 27(S2). 25–32. 1 indexed citations
5.
Timofte, Radu, et al.. (2024). mBLIP: Efficient Bootstrapping of Multilingual Vision-LLMs. 7–25. 2 indexed citations
6.
Cai, Yuanhao, Hao Bian, Jing Lin, et al.. (2023). Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement. 12470–12479. 281 indexed citations breakdown →
7.
Danelljan, Martin, et al.. (2023). PDC-Net+: Enhanced Probabilistic Dense Correspondence Network. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(8). 10247–10266. 44 indexed citations
8.
Conde, Marcos V., et al.. (2023). Towards Real-Time 4K Image Super-Resolution. 1522–1532. 28 indexed citations
9.
Liang, Jingyun, Jiezhang Cao, Guolei Sun, et al.. (2021). SwinIR: Image Restoration Using Swin Transformer. 1833–1844. 2401 indexed citations breakdown →
10.
Wei, Yunxuan, Shuhang Gu, Yawei Li, et al.. (2021). Unsupervised Real-world Image Super Resolution via Domain-distance Aware Training. 13380–13389. 96 indexed citations
11.
Li, Mu, Kai Zhang, Jinxing Li, et al.. (2021). Learning Context-Based Nonlocal Entropy Modeling for Image Compression. IEEE Transactions on Neural Networks and Learning Systems. 34(3). 1132–1145. 26 indexed citations
12.
Tripathi, Ardhendu Shekhar, Martin Danelljan, Luc Van Gool, & Radu Timofte. (2019). Tracking the Known and the Unknown by Leveraging Semantic Information.. Lirias. 292. 6 indexed citations
13.
Gu, Shuhang, Shi Guo, Wangmeng Zuo, et al.. (2019). Learned Dynamic Guidance for Depth Image Reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(10). 2437–2452. 21 indexed citations
14.
Agustsson, Eirikur, Michael Tschannen, Fabian Mentzer, Radu Timofte, & Luc Van Gool. (2018). Extreme Learned Image Compression with GANs. Computer Vision and Pattern Recognition. 2587–2590. 7 indexed citations
15.
Mentzer, Fabian, et al.. (2018). Towards Image Understanding from Deep Compression without Decoding. Lirias (KU Leuven). 4 indexed citations
16.
Agustsson, Eirikur, Fabian Mentzer, Michael Tschannen, et al.. (2017). Soft-to-hard vector quantization for end-to-end learning compressible representations. Lirias (KU Leuven). 30. 1141–1151. 77 indexed citations
17.
Agustsson, Eirikur, Fabian Mentzer, Michael Tschannen, et al.. (2017). Soft-to-Hard Vector Quantization for End-to-End Learned Compression of Images and Neural Networks.. arXiv (Cornell University). 10 indexed citations
18.
Timofte, Radu, et al.. (2013). Robust Scene Stitching in Large Scale Mobile Mapping. Lirias (KU Leuven). 107.1–107.11. 1 indexed citations
19.
Benenson, R.E., et al.. (2012). Pedestrian detection at 100 frames per second. Lirias (KU Leuven). 2903–2910. 360 indexed citations breakdown →
20.
Timofte, Radu & Luc Van Gool. (2012). Weighted collaborative representation and classification of images. Lirias (KU Leuven). 20 indexed citations

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.

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Breakdown of academic impact, for papers by Johannes Totz Breakdown of academic impact, for papers by Kyoung Mu Lee Breakdown of academic impact, for papers by Zehan Wang Breakdown of academic impact, for papers by Ferenc Huszár Breakdown of academic impact, for papers by Wenzhe Shi Breakdown of academic impact, for papers by Guangtao Zhai Breakdown of academic impact, for papers by Andrew P. Aitken Breakdown of academic impact, for papers by Weisi Lin Breakdown of academic impact, for papers by José Caballero
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