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Mario Fritz – CISPA Helmholtz Center for Information Security

Mario Fritz – CISPA Helmholtz Center for Information Security

Prof. Dr. Mario Fritz

Faculty
CISPA Helmholtz Center for Information Security

Professor
Saarland University

Fellow
European Laboratory for Learning and Intelligent Systems (ELLIS)


Google Scholar 

Semantic Scholar


We are looking for PhD students and Post-Docs! Please get in touch.

My group is working on Trustworthy Information Processing with a focus on the intersection of AI & Machine Learning with Security & Privacy.


Recent projects and initiatives related to health, privacy, AI:

  • Leading Scientist: Helmholtz Medical Security, Privacy, and AI Research Center (HMSP)
  • Coordinator and PI: Trustworthy Federated Data Analytics Project (TFDA)
  • Coordinator and PI: Protecting Genetic Data with Synthetic Cohorts from Deep Generative Models (PRO-GENE-GEN)
  • PI: Integrated Early Warning System for Local Recognition, Prevention, and Control for Epidemic Outbreaks (LOKI)
  • Partner-PI: The German Human Genome-Phenome Archive (GHGA)
  • Member of working group in “Forum Gesundheit” of BMBF: “AG Nutzbarmachung digitaler Daten für KI-Entwicklungen in der Gesundheitsforschung”

Recent work on DeepFake detecting, misinformation, attribution,and responsible disclosure:

  • CVPR’22: Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resources
  • ICLR’22: Responsible Disclosure of Generative Models Using Scalable Fingerprinting
  • ICCV’21: Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data
  • S&P’21: Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding
  • IJCAI’21: Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis
  • CVPR’21: Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs
  • ICCV’19: Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints

Recent publications:

  • ICML’22: ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
  • CVPR’22: Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resources
  • CVPR’22: B-cos Networks: Alignment is All We Need for Interpretability
  • CHIL’22: Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
  • ICLR’22: Responsible Disclosure of Generative Models Using Scalable Fingerprinting
  • ICLR’22: RelaxLoss: Defending Membership Inference Attacks without Losing Utility
  • Usenix’22: ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
  • PETS’22: Understanding Utility and Privacy of Demographic Data in Education Technology by Causal Analysis and Adversarial-Censoring
  • IJCV’21: Semantic Bottlenecks: Quantifying and Improving Inspectability of Deep Representations
  • CCS-W’21: Differential Privacy Defenses and Sampling Attacks for Membership Inference
  • CCS-W’21: “What’s in the box?!”: Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models
  • PKDD-W’21: IReEn: Reverse-Engineering of Black-Box Functions via Iterative Neural Program Synthesis
  • PKDD-W’21: SampleFix: Learning to Generate Functionally Diverse Fixes
  • ICCV’21: Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data
  • ICCV’21: Dual Contrastive Loss and Attention for GANs
  • EXCLI’21: Privacy Considerations for Sharing Genomics Data
  • IJCAI’21: Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis
  • S&P’21: Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding
  • CVPR’21: Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs
  • CVPR’21: Convolutional Dynamic Alignment Networks for Interpretable Classifications
  • CVPR’21: Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers
  • CVPR-W’21: MLCapsule: Guarded Offline Deployment of Machine Learning as a Service
  • CVPR-W’21: InfoScrub: Towards Attribute Privacy by Targeted Obfuscation
  • WACV’21: Future Moment Assessment for Action Query

Most recent work on ArXiv:

  • ArXiv’21: Backdoor Attacks on Network Certification via Data Poisoning
  • ArXiv’21: ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training

News, talks, events:

  • Scientific Advisory Board: Bosch AIShield
  • Steering Board: Helmholtz.AI
  • Recent program committees: ICML’21, NeurIPS’21, S&P’22, EuroS&P’22, CVPR’22 (AC); CCS’22
  • Runner-up Inria/CNIL Privacy Protection Prize 2020
    S&P’20 paper: “Automatically Detecting Bystanders in Photos to Reduce Privacy Risks”
  • Co-Organizers of ICLR’21 Workshop on “Synthetic Data Generation – Quality, Privacy, Bias”
  • Co-Organizers of CVPR’21 Workshop on “QuoVadis: Interdisciplinary, Socio-Technical Workshop on the Future of Computer Vision and Pattern Recognition (QuoVadis-CVPR)”
  • Co-Organizers of CVPR’21 Workshop on “Causality in Vision”
  • Founding member of Saarbrücken Artificial Intelligence & Machine Learning (SAM) unit of the European Laboratory of Learning and Intelligent Systems (ELLIS)
  • Lecturer at Digital CISPA Summer School 2020
  • Co-Organizer of Third International Workshop on The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CV-COPS) at ECCV 2020
  • Co-Organizer: 4. ACM Symposium on Computer Science in Cars: Future Challenges in Artificial Intelligence & Security for Autonomous Vehicles CSCS’20
  • Keynote at Workshop Machine Learning for Cybersecurity, ECMLPKDD’19
  • Talk at Cyber Defense Campus (CYD) Conference on Artificial Intelligence in Defence and Security
  • Co-Organizer of Second International Workshop on The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CV-COPS) at CVPR 2019
  • Co-Organizer: 3. ACM Symposium on Computer Science in Cars: Future Challenges in Artificial Intelligence & Security for Autonomous Vehicles CSCS’19
  • Leading scientist at new Helmholtz Medical Security and Privacy Research Center
  • Member of ACM Technical Policy Committee Europe
  • Mateusz Malinowski received the DAGM MVTec dissertation award as well as the Dr.-Eduard-Martin award for his PhD
  • Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

2011 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Show all

2019

Journal Articles

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

Xucong Zhang; Yusuke Sugano; Mario Fritz; Andreas Bulling

MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation Journal Article

In: Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019.

Links | BibTeX | Tags: 2017, 2018, 2019

@article{xucong19tpami,
title = {MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation},
author = {Xucong Zhang and Yusuke Sugano and Mario Fritz and Andreas Bulling},
url = {https://arxiv.org/abs/1711.09017
https://arxiv.org/pdf/1711.09017.pdf},
year = {2019},
date = {2019-02-04},
urldate = {2019-02-04},
journal = {Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
keywords = {2017, 2018, 2019},
pubstate = {published},
tppubtype = {article}
}

Close

  • https://arxiv.org/abs/1711.09017
  • https://arxiv.org/pdf/1711.09017.pdf

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2018

Journal Articles

Advanced Steel Microstructural Classification by Deep Learning Methods

Seyedmajid Azimi; Dominik Britz; Michael Engstler; Mario Fritz; Frank Mücklich

Advanced Steel Microstructural Classification by Deep Learning Methods Journal Article

In: Scientific Reports, 2018.

Links | BibTeX | Tags: 2018

@article{majid17srep,
title = {Advanced Steel Microstructural Classification by Deep Learning Methods},
author = {Seyedmajid Azimi and Dominik Britz and Michael Engstler and Mario Fritz and Frank Mücklich},
url = {https://www.nature.com/articles/s41598-018-20037-5
https://www.nature.com/articles/s41598-018-20037-5.pdf},
year = {2018},
date = {2018-02-01},
urldate = {2018-02-01},
journal = {Scientific Reports},
publisher = {Nature Publishing Group},
keywords = {2018},
pubstate = {published},
tppubtype = {article}
}

Close

  • https://www.nature.com/articles/s41598-018-20037-5
  • https://www.nature.com/articles/s41598-018-20037-5.pdf

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Reflectance and Natural Illumination from Single-Material Specular Objects Using Deep Learning

Stamatios Georgoulis; Konstantinos Rematas; Tobias Ritschel; Efstratios Gavves; Mario Fritz; Luc Van Gool; Tinne Tuytelaars

Reflectance and Natural Illumination from Single-Material Specular Objects Using Deep Learning Journal Article

In: Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.

BibTeX | Tags: 2017, 2018

@article{gergoulis18tpami,
title = {Reflectance and Natural Illumination from Single-Material Specular Objects Using Deep Learning},
author = {Stamatios Georgoulis and Konstantinos Rematas and Tobias Ritschel and Efstratios Gavves and Mario Fritz and Luc Van Gool and Tinne Tuytelaars},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
journal = {Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
keywords = {2017, 2018},
pubstate = {published},
tppubtype = {article}
}

Close

Inproceedings

Adversarial Scene Editing: Automatic Object Removal from Weak Supervision

Rakshith Shetty; Mario Fritz; Bernt Schiele

Adversarial Scene Editing: Automatic Object Removal from Weak Supervision Inproceedings

In: Neural Information Processing Systems (NIPS), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{shetty18nips,
title = {Adversarial Scene Editing: Automatic Object Removal from Weak Supervision },
author = {Rakshith Shetty and Mario Fritz and Bernt Schiele},
url = {preliminary:
https://arxiv.org/abs/1806.01911
https://arxiv.org/pdf/1806.01911.pdf},
year = {2018},
date = {2018-12-03},
booktitle = {Neural Information Processing Systems (NIPS)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • preliminary:
  • https://arxiv.org/abs/1806.01911
  • https://arxiv.org/pdf/1806.01911.pdf

Close

Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes

Yang He; Bernt Schiele; Mario Fritz

Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes Inproceedings

In: European Conference on Computer Vision (ECCV), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{he18eccv,
title = {Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes},
author = {Yang He and Bernt Schiele and Mario Fritz},
url = {http://openaccess.thecvf.com/content_ECCV_2018/papers/Yang_He_Diverse_Conditional_Image_ECCV_2018_paper.pdf},
year = {2018},
date = {2018-09-12},
booktitle = {European Conference on Computer Vision (ECCV)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • http://openaccess.thecvf.com/content_ECCV_2018/papers/Yang_He_Diverse_Conditiona[...]

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A Hybrid Model for Identity Obfuscation by Face Replacement

Qianru Sun; Ayush Tewari; Weipeng Xu; Mario Fritz; Christian Theobalt; Bernt Schiele

A Hybrid Model for Identity Obfuscation by Face Replacement Inproceedings

In: European Conference on Computer Vision, 2018.

Links | BibTeX | Tags: 2018

@inproceedings{sun18eccv,
title = {A Hybrid Model for Identity Obfuscation by Face Replacement},
author = {Qianru Sun and Ayush Tewari and Weipeng Xu and Mario Fritz and Christian Theobalt and Bernt Schiele},
url = {https://arxiv.org/abs/1804.04779
https://arxiv.org/pdf/1804.04779.pdf},
year = {2018},
date = {2018-09-09},
booktitle = {European Conference on Computer Vision},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • https://arxiv.org/abs/1804.04779
  • https://arxiv.org/pdf/1804.04779.pdf

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Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions

Misha Wagner; Hector Basevi; Rakshith Shetty; Wenbin Li; Mateusz Malinowski; Mario Fritz; Ales Leonardis

Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions Inproceedings

In: Visual Learning and Embodied Agents in Simulation Environments Workshop at European Conference on Computer Vision, 2018.

Links | BibTeX | Tags: 2018

@inproceedings{wagner18eccvw,
title = {Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions},
author = {Misha Wagner and Hector Basevi and Rakshith Shetty and Wenbin Li and Mateusz Malinowski and Mario Fritz and Ales Leonardis},
url = {https://arxiv.org/abs/1809.03707
https://arxiv.org/pdf/1809.03707.pdf},
year = {2018},
date = {2018-09-08},
booktitle = {Visual Learning and Embodied Agents in Simulation Environments Workshop at European Conference on Computer Vision},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • https://arxiv.org/abs/1809.03707
  • https://arxiv.org/pdf/1809.03707.pdf

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Sequential Attacks on Agents for Long-Term Adversarial Goals

Edgar Tretschk; Seong Joon Oh; Mario Fritz

Sequential Attacks on Agents for Long-Term Adversarial Goals Inproceedings

In: 2. ACM Computer Science in Cars Symposium -- Future Challenges in Artificial Intelligence & Security for Autonomous Vehicles, 2018.

BibTeX | Tags: 2018

@inproceedings{edgar18cscs,
title = {Sequential Attacks on Agents for Long-Term Adversarial Goals},
author = {Edgar Tretschk and Seong Joon Oh and Mario Fritz}},
year = {2018},
date = {2018-09-01},
booktitle = {2. ACM Computer Science in Cars Symposium -- Future Challenges in Artificial Intelligence & Security for Autonomous Vehicles},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

A4NT: Author Attribute Anonymity by Adversarial Training of Neural Machine Translation

Rakshith Shetty; Bernt Schiele; Mario Fritz

A4NT: Author Attribute Anonymity by Adversarial Training of Neural Machine Translation Inproceedings

In: 27th USENIX Security Symposium (USENIX Security 18), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{usenix18rakshith,
title = {A4NT: Author Attribute Anonymity by Adversarial Training of Neural Machine Translation},
author = {Rakshith Shetty and Bernt Schiele and Mario Fritz},
url = {preliminary version:
https://arxiv.org/abs/1711.01921
https://arxiv.org/pdf/1711.01921.pdf
},
year = {2018},
date = {2018-08-17},
urldate = {2018-08-17},
booktitle = {27th USENIX Security Symposium (USENIX Security 18)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • preliminary version:
  • https://arxiv.org/abs/1711.01921
  • https://arxiv.org/pdf/1711.01921.pdf

Close

Accurate and Diverse Sampling of Sequences based on a “Best of Many” Sample Objective

Apratim Bhattacharyya; Bernt Schiele; Mario Fritz

Accurate and Diverse Sampling of Sequences based on a “Best of Many” Sample Objective Inproceedings

In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{apratim18cvprb,
title = {Accurate and Diverse Sampling of Sequences based on a “Best of Many” Sample Objective},
author = {Apratim Bhattacharyya and Bernt Schiele and Mario Fritz},
url = {http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/3890.pdf},
year = {2018},
date = {2018-06-22},
urldate = {2018-06-22},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/3890.pdf

Close

Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images

Tribhuvanesh Orekondy; Mario Fritz; Bernt Schiele

Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images Inproceedings

In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{tribhu18cvpr,
title = {Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images},
author = {Tribhuvanesh Orekondy and Mario Fritz and Bernt Schiele},
url = {https://arxiv.org/abs/1712.01066
https://arxiv.org/pdf/1712.01066.pdf},
year = {2018},
date = {2018-06-18},
urldate = {2018-06-18},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • https://arxiv.org/abs/1712.01066
  • https://arxiv.org/pdf/1712.01066.pdf

Close

Natural and Effective Obfuscation by Head Inpainting

Qianru Sun; Liqian Ma; Seong Joon Oh; Luc Van Gool; Bernt Schiele; Mario Fritz

Natural and Effective Obfuscation by Head Inpainting Inproceedings

In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{sun18cvpr,
title = {Natural and Effective Obfuscation by Head Inpainting},
author = {Qianru Sun and Liqian Ma and Seong Joon Oh and Luc Van Gool and Bernt Schiele and Mario Fritz},
url = {https://arxiv.org/abs/1711.09001
https://arxiv.org/pdf/1711.09001.pdf},
year = {2018},
date = {2018-06-18},
urldate = {2018-06-18},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • https://arxiv.org/abs/1711.09001
  • https://arxiv.org/pdf/1711.09001.pdf

Close

Disentangled Person Image Generation

Liqian Ma; Qianru Sun; Stamatios Georgoulis; Luc Van Gool; Bernt Schiele; Mario Fritz

Disentangled Person Image Generation Inproceedings

In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{ma18cvpr,
title = {Disentangled Person Image Generation },
author = {Liqian Ma and Qianru Sun and Stamatios Georgoulis and Luc Van Gool and Bernt Schiele and Mario Fritz},
url = {https://arxiv.org/abs/1712.02621
https://arxiv.org/pdf/1712.02621.pdf},
year = {2018},
date = {2018-06-18},
urldate = {2018-06-18},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • https://arxiv.org/abs/1712.02621
  • https://arxiv.org/pdf/1712.02621.pdf

Close

Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty

Apratim Bhattacharyya; Mario Fritz; Bernt Schiele

Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty Inproceedings

In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{apratim18cvpr,
title = {Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty},
author = {Apratim Bhattacharyya and Mario Fritz and Bernt Schiele},
url = {https://arxiv.org/abs/1711.09026
https://arxiv.org/pdf/1711.09026.pdf},
year = {2018},
date = {2018-06-18},
urldate = {2018-06-18},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • https://arxiv.org/abs/1711.09026
  • https://arxiv.org/pdf/1711.09026.pdf

Close

Towards Reverse-Engineering Black-Box Neural Networks

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

Towards Reverse-Engineering Black-Box Neural Networks Inproceedings

In: Internation Conference on Representation Learning (ICLR), 2018, (to appear).

Links | BibTeX | Tags: 2018

@inproceedings{joon18icrl,
title = {Towards Reverse-Engineering Black-Box Neural Networks},
author = {Seong Joon Oh and Max Augustin and Bernt Schiele and Mario Fritz},
url = {https://github.com/coallaoh/WhitenBlackBox
https://arxiv.org/abs/1711.01768
https://arxiv.org/pdf/1711.01768.pdf},
year = {2018},
date = {2018-04-30},
urldate = {2018-04-30},
booktitle = {Internation Conference on Representation Learning (ICLR)},
note = {to appear},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • https://github.com/coallaoh/WhitenBlackBox
  • https://arxiv.org/abs/1711.01768
  • https://arxiv.org/pdf/1711.01768.pdf

Close

Long-Term Image Boundary Prediction

Apratim Bhattacharyya; Mateusz Malinowski; Bernt Schiele; Mario Fritz

Long-Term Image Boundary Prediction Inproceedings

In: Association for the Advancement of Artificial Intelligence (AAAI), 2018.

Links | BibTeX | Tags: 2018

@inproceedings{apratim18aaai,
title = {Long-Term Image Boundary Prediction},
author = {Apratim Bhattacharyya and Mateusz Malinowski and Bernt Schiele and Mario Fritz},
url = {https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewFile/17280/16540},
year = {2018},
date = {2018-02-02},
urldate = {2018-02-02},
booktitle = {Association for the Advancement of Artificial Intelligence (AAAI)},
keywords = {2018},
pubstate = {published},
tppubtype = {inproceedings}
}

Close

  • https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewFile/17280/16540

Close

Technical Reports

Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation

Rakshith Shetty; Bernt Schiele; Mario Fritz

Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation Technical Report

arXiv:1812.06707, 2018.

Links | BibTeX | Tags: 2018

@techreport{shetty8arxiv,
title = {Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation},
author = {Rakshith Shetty and Bernt Schiele and Mario Fritz},
url = {https://arxiv.org/abs/1812.06707
https://arxiv.org/pdf/1812.06707.pdf},
year = {2018},
date = {2018-12-17},
type = {arXiv:1812.06707},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

Close

  • https://arxiv.org/abs/1812.06707
  • https://arxiv.org/pdf/1812.06707.pdf

Close

Knockoff Nets: Stealing Functionality of Black-Box Models

Tribhuvanesh Orekondy; Bernt Schiele; Mario Fritz

Knockoff Nets: Stealing Functionality of Black-Box Models Technical Report

arXiv:1812.02766, 2018.

Links | BibTeX | Tags: 2018

@techreport{tribhu18arxivb,
title = {Knockoff Nets: Stealing Functionality of Black-Box Models},
author = {Tribhuvanesh Orekondy and Bernt Schiele and Mario Fritz},
url = {https://arxiv.org/abs/1812.02766
https://arxiv.org/pdf/1812.02766.pdf
},
year = {2018},
date = {2018-12-10},
type = {arXiv:1812.02766},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

Close

  • https://arxiv.org/abs/1812.02766
  • https://arxiv.org/pdf/1812.02766.pdf

Close

Attributing Fake Images to GANs: Analyzing Fingerprints in Generated Images

Ning Yu; Larry Davis; Mario Fritz

Attributing Fake Images to GANs: Analyzing Fingerprints in Generated Images Technical Report

2018.

Links | BibTeX | Tags: 2018

@techreport{yu18arxiv,
title = {Attributing Fake Images to GANs: Analyzing Fingerprints in Generated Images},
author = {Ning Yu and Larry Davis and Mario Fritz},
url = {https://arxiv.org/abs/1811.08180
https://arxiv.org/pdf/1811.08180.pdf},
year = {2018},
date = {2018-11-21},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

Close

  • https://arxiv.org/abs/1811.08180
  • https://arxiv.org/pdf/1811.08180.pdf

Close

MLCapsule: Guarded Offline Deployment of Machine Learning as a Service

Lucjan Hanzlik; Yang Zhang; Kathrin Grosse; Ahmed Salem; Max Augustin; Michael Backes; Mario Fritz

MLCapsule: Guarded Offline Deployment of Machine Learning as a Service Technical Report

arXiv:1808.00590 [cs.CR], 2018.

Links | BibTeX | Tags: 2018

@techreport{hanzlik18arixv,
title = {MLCapsule: Guarded Offline Deployment of Machine Learning as a Service},
author = {Lucjan Hanzlik and Yang Zhang and Kathrin Grosse and Ahmed Salem and Max Augustin and Michael Backes and Mario Fritz},
url = {https://arxiv.org/abs/1808.00590
https://arxiv.org/pdf/1808.00590.pdf},
year = {2018},
date = {2018-08-03},
type = {arXiv:1808.00590 [cs.CR]},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

Close

  • https://arxiv.org/abs/1808.00590
  • https://arxiv.org/pdf/1808.00590.pdf

Close

Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources

Hosnieh Sattar; Gerard Pons-Moll; Mario Fritz

Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources Technical Report

arXiv:1807.03235, 2018.

Links | BibTeX | Tags: 2018

@techreport{sattar18arxiv,
title = {Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources},
author = {Hosnieh Sattar and Gerard Pons-Moll and Mario Fritz},
url = {//arxiv.org/abs/1807.03235
//arxiv.org/pdf/1807.03235.pdf
},
year = {2018},
date = {2018-07-10},
urldate = {2018-07-10},
type = {arXiv:1807.03235},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

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  • //arxiv.org/abs/1807.03235
  • //arxiv.org/pdf/1807.03235.pdf

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

Ahmed Salem; Yang Zhang; Mathias Humbert; Mario Fritz; Michael Backes

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

arXiv:1806.01246 [cs.CR], 2018.

Links | BibTeX | Tags: 2018

@techreport{salem18arxiv,
title = {ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models},
author = {Ahmed Salem and Yang Zhang and Mathias Humbert and Mario Fritz and Michael Backes},
url = {https://arxiv.org/abs/1806.01246
https://arxiv.org/pdf/1806.01246.pdf
},
year = {2018},
date = {2018-06-05},
type = {arXiv:1806.01246 [cs.CR]},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

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  • https://arxiv.org/abs/1806.01246
  • https://arxiv.org/pdf/1806.01246.pdf

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Adversarial Scene Editing: Automatic Object Removal from Weak Supervision

Rakshith Shetty; Mario Fritz; Bernt Schiele

Adversarial Scene Editing: Automatic Object Removal from Weak Supervision Technical Report

2018.

Links | BibTeX | Tags: 2018

@techreport{rakshith18arxiv,
title = {Adversarial Scene Editing: Automatic Object Removal from Weak Supervision},
author = {Rakshith Shetty and Mario Fritz and Bernt Schiele},
url = {https://arxiv.org/abs/1806.01911
https://arxiv.org/pdf/1806.01911.pdf},
year = {2018},
date = {2018-06-05},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

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  • https://arxiv.org/abs/1806.01911
  • https://arxiv.org/pdf/1806.01911.pdf

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Sequential Attacks on Agents for Long-Term Adversarial Goals

Edgar Tretschk; Seong Joon Oh; Mario Fritz

Sequential Attacks on Agents for Long-Term Adversarial Goals Technical Report

arXiv:1805.12487, 2018.

Links | BibTeX | Tags: 2018

@techreport{tretschk18arxiv,
title = {Sequential Attacks on Agents for Long-Term Adversarial Goals},
author = {Edgar Tretschk and Seong Joon Oh and Mario Fritz},
url = {https://arxiv.org/abs/1805.12487
https://arxiv.org/pdf/1805.12487.pdf
},
year = {2018},
date = {2018-05-31},
type = {arXiv:1805.12487},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

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  • https://arxiv.org/abs/1805.12487
  • https://arxiv.org/pdf/1805.12487.pdf

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Understanding and Controlling User Linkability in Decentralized Learning

Tribhuvanesh Orekondy; Seong Joon Oh; Bernt Schiele; Mario Fritz

Understanding and Controlling User Linkability in Decentralized Learning Technical Report

arXiv:1805.05838 [cs.CR], 2018.

Links | BibTeX | Tags: 2018

@techreport{tribhu18arxiv,
title = {Understanding and Controlling User Linkability in Decentralized Learning},
author = {Tribhuvanesh Orekondy and Seong Joon Oh and Bernt Schiele and Mario Fritz},
url = {https://arxiv.org/abs/1805.05838
https://arxiv.org/pdf/1805.05838.pdf},
year = {2018},
date = {2018-05-16},
urldate = {2018-05-16},
type = {arXiv:1805.05838 [cs.CR]},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

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  • https://arxiv.org/abs/1805.05838
  • https://arxiv.org/pdf/1805.05838.pdf

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A Hybrid Model for Identity Obfuscation by Face Replacement

Qianru Sun; Ayush Tewari; Weipeng Xu; Mario Fritz; Christian Theobalt; Bernt Schiele

A Hybrid Model for Identity Obfuscation by Face Replacement Technical Report

arXiv:1804.04779 [cs.CV], 2018.

Links | BibTeX | Tags: 2018

@techreport{sun18arxiv,
title = {A Hybrid Model for Identity Obfuscation by Face Replacement},
author = {Qianru Sun and Ayush Tewari and Weipeng Xu and Mario Fritz and Christian Theobalt and Bernt Schiele},
url = {https://arxiv.org/abs/1804.04779
https://arxiv.org/pdf/1804.04779.pdf},
year = {2018},
date = {2018-04-13},
urldate = {2018-04-13},
type = {arXiv:1804.04779 [cs.CV]},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

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  • https://arxiv.org/abs/1804.04779
  • https://arxiv.org/pdf/1804.04779.pdf

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Deep Appearance Maps

Maxim Maximov; Tobias Ritschel; Mario Fritz

Deep Appearance Maps Technical Report

arXiv:1804.00863 [cs.CV], 2018.

Links | BibTeX | Tags: 2018

@techreport{maximov18arxiv,
title = {Deep Appearance Maps},
author = {Maxim Maximov and Tobias Ritschel and Mario Fritz},
url = {https://arxiv.org/abs/1804.00863
https://arxiv.org/pdf/1804.00863.pdf},
year = {2018},
date = {2018-04-03},
urldate = {2018-04-03},
type = {arXiv:1804.00863 [cs.CV]},
keywords = {2018},
pubstate = {published},
tppubtype = {techreport}
}

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  • https://arxiv.org/abs/1804.00863
  • https://arxiv.org/pdf/1804.00863.pdf

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