Andreas Lugmayr

2.1k total citations · 1 hit paper
6 papers, 932 citations indexed

About

Andreas Lugmayr is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Andreas Lugmayr has authored 6 papers receiving a total of 932 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 2 papers in Media Technology and 1 paper in Computer Graphics and Computer-Aided Design. Recurrent topics in Andreas Lugmayr's work include Advanced Image Processing Techniques (5 papers), Advanced Vision and Imaging (4 papers) and Image and Signal Denoising Methods (2 papers). Andreas Lugmayr is often cited by papers focused on Advanced Image Processing Techniques (5 papers), Advanced Vision and Imaging (4 papers) and Image and Signal Denoising Methods (2 papers). Andreas Lugmayr collaborates with scholars based in Switzerland, United States and Belgium. Andreas Lugmayr's co-authors include Radu Timofte, Martin Danelljan, Luc Van Gool, Fisher Yu, Andrés Romero, Kai Zhang, Jingyun Liang, Julien Lamour, Shuhang Gu and Cong Wang and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

In The Last Decade

Andreas Lugmayr

6 papers receiving 901 citations

Hit Papers

align trajectories

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.

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

2022 797 citations Andreas Lugmayr, Martin Danelljan et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andreas Lugmayr Switzerland	5	671	137	117	108	95	6	932
Andrés Romero France	6	594 0.9×	149 1.1×	117 1.0×	76 0.7×	94 1.0×	14	869
Chitwan Saharia United States	6	838 1.2×	169 1.2×	103 0.9×	247 2.3×	91 1.0×	7	1.2k
Yunjey Choi South Korea	5	970 1.4×	211 1.5×	138 1.2×	58 0.5×	64 0.7×	6	1.1k
Youngjung Uh South Korea	9	1.2k 1.9×	276 2.0×	175 1.5×	87 0.8×	75 0.8×	35	1.4k
Yongcheng Jing China	10	670 1.0×	180 1.3×	126 1.1×	66 0.6×	56 0.6×	16	859
Jeff Orchard Canada	16	461 0.7×	156 1.1×	57 0.5×	120 1.1×	46 0.5×	49	877
Jiahao Pang Hong Kong	15	857 1.3×	162 1.2×	90 0.8×	212 2.0×	221 2.3×	44	1.1k
Arsenii Ashukha Russia	4	520 0.8×	181 1.3×	93 0.8×	59 0.5×	52 0.5×	6	694
Junhao Zhang China	13	482 0.7×	167 1.2×	35 0.3×	120 1.1×	84 0.9×	61	877
E. Sharon Israel	10	802 1.2×	128 0.9×	51 0.4×	123 1.1×	141 1.5×	14	1.0k

Countries citing papers authored by Andreas Lugmayr

Since Specialization

Citations

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

Fields of papers citing papers by Andreas Lugmayr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Lugmayr

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Lugmayr. A scholar is included among the top collaborators of Andreas Lugmayr 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 Andreas Lugmayr. Andreas Lugmayr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Valanarasu, Jeya Maria Jose, Rahul Garg, Xin Tong, et al.. (2025). ReBotNet: Fast Real-Time Video Enhancement. 1424–1435. 2 indexed citations

2.

Lugmayr, Andreas, Martin Danelljan, Andrés Romero, et al.. (2022). RePaint: Inpainting using Denoising Diffusion Probabilistic Models. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 11451–11461. 797 indexed citations breakdown →

3.

Lugmayr, Andreas, Martin Danelljan, Fisher Yu, Luc Van Gool, & Radu Timofte. (2022). Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 874–883. 7 indexed citations

4.

Lugmayr, Andreas, Martin Danelljan, Radu Timofte, et al.. (2022). NTIRE 2022 Challenge on Learning the Super-Resolution Space. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 785–796. 10 indexed citations

5.

Liang, Jingyun, Andreas Lugmayr, Kai Zhang, et al.. (2021). Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 4056–4065. 73 indexed citations

6.

Gu, Shuhang, et al.. (2019). DIV8K: DIVerse 8K Resolution Image Dataset. 3512–3516. 43 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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