2026 Mario Fritz: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	72	1667	1616	67	66	251	22041

Mario Fritz publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Mario Fritz sits on this spectrum.

32 publications 991+

This scientist: 251 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Mario Fritz D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Mario Fritz sits on this spectrum.

30 D-Index 131+

This scientist: 72 D-Index — 89th percentile

89% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

2025 - Research.com Computer Science in Germany Leader Award
2023 - Research.com Computer Science in Germany Leader Award
2022 - Research.com Computer Science in Germany Leader Award

Overview

Mario Fritz is affiliated with the Helmholtz Center for Information Security in Germany. Their research primarily falls within the field of Computer Science, with a substantial focus on Artificial Intelligence, Computer Vision and Pattern Recognition, and related subfields.

The scientist's work covers a range of main topics including:

Adversarial Robustness in Machine Learning
Privacy-Preserving Technologies in Data
Generative Adversarial Networks and Image Synthesis
Advanced Neural Network Applications
Explainable Artificial Intelligence (XAI)
Digital Media Forensic Detection
Anomaly Detection Techniques and Applications

Recent significant publications by Mario Fritz include:

"Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
"Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resources," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
"A4NT: Author Attribute Anonymity by Adversarial Training of Neural Machine Translation," 2023, MPG.PuRe (Max Planck Society)
"Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks," 2023, arXiv (Cornell University)
"GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators," 2023, OPAL (Open@LaTrobe) (La Trobe University)

Mario Fritz frequently collaborates with several coauthors, including:

Bernt Schiele
Sahar Abdelnabi
Dingfan Chen
Raouf Kerkouche
Ning Yu

The scientist has contributed extensively to various academic venues, with a notable number of publications in:

arXiv (Cornell University)
Proceedings on Privacy Enhancing Technologies
Lecture Notes in Computer Science
MPG.PuRe (Max Planck Society)
OPAL (Open@LaTrobe) (La Trobe University)

In terms of book contributions, Mario Fritz has published with La Trobe University, including:

"Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany, October 9-12, 2018, Proceedings," published in 2023

Best Publications

Adapting visual category models to new domains

Kate Saenko;Brian Kulis;Mario Fritz;Trevor Darrell

3019
Citations
Appearance-based gaze estimation in the wild

Xucong Zhang;Yusuke Sugano;Mario Fritz;Andreas Bulling

911
Citations
Ask Your Neurons: A Neural-Based Approach to Answering Questions about Images

Mateusz Malinowski;Marcus Rohrbach;Mario Fritz

718
Citations
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

Ahmed Salem;Yang Zhang;Mathias Humbert;Pascal Berrang

616
Citations
A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input

Mateusz Malinowski;Mario Fritz

609
Citations
Discovery of activity patterns using topic models

Tâm Huynh;Mario Fritz;Bernt Schiele

603
Citations
Disentangled Person Image Generation

Liqian Ma;Qianru Sun;Stamatios Georgoulis;Luc Van Gool

553
Citations
MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation

Xucong Zhang;Yusuke Sugano;Mario Fritz;Andreas Bulling

550
Citations
A Category-Level 3D Object Dataset: Putting the Kinect to Work.

Allison Janoch;Sergey Karayev;Yangqing Jia;Jonathan T. Barron

533
Citations
The 2005 PASCAL visual object classes challenge

Mark Everingham;Andrew Zisserman;Christopher K. I. Williams;Luc Van Gool

514
Citations
Towards Reverse-Engineering Black-Box Neural Networks

Seong Joon Oh;Bernt Schiele;Mario Fritz

504
Citations
Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints

Ning Yu;Larry Davis;Mario Fritz

474
Citations
Advanced Steel Microstructural Classification by Deep Learning Methods.

Seyed Majid Azimi;Seyed Majid Azimi;Dominik Britz;Michael Engstler;Mario Fritz

462
Citations
It’s Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation

Xucong Zhang;Yusuke Sugano;Mario Fritz;Andreas Bulling

458
Citations
On the Significance of Real‐World Conditions for Material Classification

Eric Hayman;Barbara Caputo;Mario Fritz;Jan Olof Eklundh

451
Citations
Knockoff Nets: Stealing Functionality of Black-Box Models

Tribhuvanesh Orekondy;Bernt Schiele;Mario Fritz

445
Citations
A category-level 3-D object dataset: Putting the Kinect to work

Allison Janoch;Sergey Karayev;Yangqing Jia;Jonathan T. Barron

391
Citations
Not What You've Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection

Unknown

292
Citations
VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

Abhishek Sharma;Oliver Grau;Mario Fritz

283
Citations
A geometric approach to robotic laundry folding

Stephen Miller;Jur Van Den Berg;Mario Fritz;Trevor Darrell

275
Citations
Towards Reverse-Engineering Black-Box Neural Networks

Seong Joon Oh;Max Augustin;Bernt Schiele;Mario Fritz

76
Citations

Frequent Co-Authors

Bernt Schiele Max Planck Institute for Informatics

Trevor Darrell University of California, Berkeley

Andreas Bulling University of Stuttgart

Tinne Tuytelaars KU Leuven

Tobias Ritschel University College London

Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)

Ales Leonardis University of Birmingham

Rodrigo Benenson Google (United States)

Kate Saenko Boston University

Qianru Sun Singapore Management University

External Links

Personal website of Mario Fritz Google Scholar page

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