Paul Bergmann

4.3k total citations · 3 hit papers
9 papers, 2.2k citations indexed

About

Paul Bergmann is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Industrial and Manufacturing Engineering. According to data from OpenAlex, Paul Bergmann has authored 9 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Industrial and Manufacturing Engineering. Recurrent topics in Paul Bergmann's work include Anomaly Detection Techniques and Applications (7 papers), Industrial Vision Systems and Defect Detection (4 papers) and 3D Surveying and Cultural Heritage (2 papers). Paul Bergmann is often cited by papers focused on Anomaly Detection Techniques and Applications (7 papers), Industrial Vision Systems and Defect Detection (4 papers) and 3D Surveying and Cultural Heritage (2 papers). Paul Bergmann collaborates with scholars based in Germany and Netherlands. Paul Bergmann's co-authors include David Sattlegger, Carsten Steger, Michael Fauser, Sindy Löwe, Xin Jin, Bertram Drost and Markus Ulrich and has published in prestigious journals such as International Journal of Computer Vision, arXiv (Cornell University) and 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

In The Last Decade

Paul Bergmann

9 papers receiving 2.1k citations

Hit Papers

MVTec AD — A Comprehensive Real-World Dataset for Unsuper... 2019 2026 2021 2023 2019 2020 2021 250 500 750
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. MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection
    2019 938 citations Paul Bergmann, Michael Fauser et al. profile →
  2. Uninformed Students: Student-Teacher Anomaly Detection With Discriminative Latent Embeddings
    2020 489 citations Paul Bergmann, Michael Fauser et al. arXiv (Cornell University) profile →
  3. The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection
    2021 251 citations Paul Bergmann, Michael Fauser et al. International Journal of Computer Vision profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul Bergmann Germany 9 1.6k 704 634 454 293 9 2.2k
David Sattlegger Germany 7 1.6k 1.0× 685 1.0× 584 0.9× 448 1.0× 243 0.8× 7 2.1k
Michael Fauser Germany 6 1.5k 0.9× 638 0.9× 546 0.9× 430 0.9× 222 0.8× 6 2.0k
Dong Gong China 17 1.0k 0.6× 112 0.2× 1.1k 1.7× 488 1.1× 107 0.4× 43 2.0k
Budhaditya Saha Australia 10 1.2k 0.8× 96 0.1× 503 0.8× 622 1.4× 117 0.4× 19 1.5k
Moussa Reda Mansour Brazil 9 1.1k 0.7× 97 0.1× 447 0.7× 599 1.3× 153 0.5× 19 1.4k
Weixin Luo China 20 2.4k 1.5× 28 0.0× 1.7k 2.6× 1.4k 3.2× 73 0.2× 30 3.1k
Yangfan Li China 19 246 0.2× 55 0.1× 255 0.4× 274 0.6× 168 0.6× 73 1.2k
Claudio Piciarelli Italy 21 658 0.4× 42 0.1× 876 1.4× 292 0.6× 42 0.1× 54 1.4k
Abdellatif Mtibaa Tunisia 21 398 0.3× 49 0.1× 838 1.3× 145 0.3× 193 0.7× 179 1.7k
Paolo Valigi Italy 24 200 0.1× 198 0.3× 628 1.0× 113 0.2× 945 3.2× 152 2.3k

Countries citing papers authored by Paul Bergmann

Since Specialization
Citations

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

Fields of papers citing papers by Paul Bergmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Bergmann

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

All Works

9 of 9 papers shown
1.
Bergmann, Paul & David Sattlegger. (2023). Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2612–2622. 42 indexed citations
2.
3.
Bergmann, Paul, Xin Jin, David Sattlegger, & Carsten Steger. (2022). The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization. arXiv (Cornell University). 202–213. 83 indexed citations
4.
Bergmann, Paul, et al.. (2022). Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization. International Journal of Computer Vision. 130(4). 947–969. 97 indexed citations
5.
Bergmann, Paul, et al.. (2021). The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection. International Journal of Computer Vision. 129(4). 1038–1059. 251 indexed citations breakdown →
6.
Bergmann, Paul, Michael Fauser, David Sattlegger, & Carsten Steger. (2020). Uninformed Students: Student-Teacher Anomaly Detection With Discriminative Latent Embeddings. arXiv (Cornell University). 4182–4191. 489 indexed citations breakdown →
7.
Bergmann, Paul, Michael Fauser, David Sattlegger, & Carsten Steger. (2019). MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection. 9584–9592. 938 indexed citations breakdown →
8.
Bergmann, Paul, Sindy Löwe, Michael Fauser, David Sattlegger, & Carsten Steger. (2019). Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders. 372–380. 187 indexed citations
9.
Drost, Bertram, et al.. (2017). Introducing MVTec ITODD — A Dataset for 3D Object Recognition in Industry. 2200–2208. 89 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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