Prof. Dr. Mario Fritz Faculty CISPA Helmholtz Center for Information Security Professor University of Saarland Google Scholar  Semantic Scholar

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

Recent publications:

• USENIX Security’20: Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning

• TPAMI’19: Person Recognition in Personal Photo Collections
• Explainable AI Book: Towards reverse-engineering black-box neural networks
• PriML@NeurIPS’19: Differential Privacy Defenses and Sampling Attacks for Membership Inference
• PriML@NeurIPS’19: GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs
• FL@NeurIPS’19: Gradient-Leaks: Understanding Deanonymization in Federated Learning
• BDL@NeurIPS’19: Conditional Flow Variational Autoencoders for Structured Sequence Prediction
• BDL@NeurIPS’19: “Best of Many” Samples Distribution Matching
• HotPETs’19: Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning
• PUT@PETs’19: Understanding and Recognizing Bystanders in Images for Privacy Protection
• ICCV’19: Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints
• ICCV’19: Deep Appearance Maps
• CVPR’19: Knockoff Nets: Stealing Functionality of Black-Box Models
• CVPR’19: Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation
• CVPR’19: Time-Conditioned Action Anticipation in One Shot
• ICLR’19: Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods
• NDSS’19: ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
• WACV’19: Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources
• TPAMI’19: MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation

• NIPS’18: Adversarial Scene Editing: Automatic Object Removal from Weak Supervision
• ECCV’18: A Hybrid Model for Identity Obfuscation by Face Replacement
• ECCV’18: Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes
• ECCV-W’18: Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions
• CSCS’18: Sequential Attacks on Agents for Long-Term Adversarial Goals
• USENIX Security’18: A4NT: Author Attribute Anonymity by Adversarial Training of Neural Networks
• CVPR’18: Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images
• CVPR’18: Natural and Effective Obfuscation by Head Inpainting
• CVPR’18: Disentangled Person Image Generation
• CVPR’18: Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty
• CVPR’18: Accurate and Diverse Sampling of Sequences based on a “Best of Many” Sample Objective
• ICLR’18: Towards Reverse-Engineering Black-Box Neural Networks
• Scientific Reports’18: Advanced Steel Microstructural Classification by Deep Learning Methods
• AAAI’18: Long-Term Image Boundary Prediction
• TPAMI’18: Reflectance and Natural Illumination from Single-Material Specular Objects Using Deep Learning

Most recent work on ArXiv:

• ArXiv’19: “Best-of-Many-Samples” Distribution Matching
• ArXiv’19: WhiteNet: Phishing Website Detection by Visual Whitelists
• ArXiv’19: Interpretability Beyond Classification Output: Semantic Bottleneck Networks
• ArXiv’19: Prediction Poisoning: Utility-Constrained Defenses Against Model Stealing Attacks
• ArXiv’19: SampleFix: Learning to Correct Programs by Sampling Diverse Fixes
• ArXiv’19: Shape Evasion: Preventing Body Shape Inference of Multi-Stage Approaches
• ArXiv’19: Learning Manipulation under Physics Constraints with Visual Perception
• ArXiv’18: MLCapsule: Guarded Offline Deployment of Machine Learning as a Service
• ArXiv’18: Understanding and Controlling User Linkability in Decentralized Learning

News, talks, events:

• 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)
• Talk on “Challenges of Disruptive Technologies (BigData/AI)  for MINT Education” at “MINT Conference: MINT Education towards 2028“
• Talk at “Sommer der Cybersicherheit“, Congresshalle, Saarbrücken
• Co-Organizer: new Conference on Future Challenges in
  Artificial Intelligence & Security for Autonomous Vehicles CSCS’18
• Co-Organizer of Workshop  on Interactive and Adaptive Learning in an Open World at ECCV’18
• 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 2018
• Invited talk Center for Art and Media, Karlsruhe, 2018
  “The Bright and Dark Side of Computer Vision: Latest Advances and Implications on Privacy”
• Program Chair of German Conference on Pattern Recognition GCPR 2018
• Invited talk at First International Workshop on The Bright and Dark Sides of Computer Vision:
  Challenges and Opportunities for Privacy and Security at CVPR 2017
  “Towards a Visual Privacy Advisor: Understanding and Controlling Privacy Risks in Visual Data”
• Invited talk at ACM Chapters Computer Science in Cars Symposium, 2017
• Invited talk at Symposium on Image Forensics and Identification, 2017
  “Re-Identification with Deep Learning”

---

2013 2014 2015 2016 2017 2018 2019 b3do bayesian bmvc google glass iccv iclr mateusz mri optimization ubic ubici

All years 20192018201720162015201420132012201120102009200820072006200520042002 All types Journal ArticlesIncollectionsInproceedingsMasters ThesesMiscellaneousPhD ThesesProceedingsTechnical ReportsWorkshops All authors Sahar AbdelnabiPaarijaat AdityaZeynep AkataOliver AmftApratim Bhattacharyya, Mateusz Malinowski, Mario FritzMax AugustinSeyed Majid AzimiSeyedmajid AzimiSeyedmajid Azimi and Dominik Britz and Michael Engstler and Mario Fritz and Frank MücklichMichael BackesHector BaseviRodrigo BenensonBobby BhattacharjeeApratim BhattacharyaApratim BhattacharyyaJeannette BohgDominik BritzAndreas BullingDingfan ChenWei-Chen ChiuSreyasi Nag ChowdhuryDavid CrandallTrevor DarrellLarry DavisPeter DruschelMichael EngstlerMario FritzMario FritzFabio GalassoEfstratios GavvesStamatios GeorgoulisDaniel GoehringLuc Van GoolOliver GrauKathrin GrosseHossein HajipourMichael HanselmannLucjan HanzlikRakibul HasanYang HeLisa Anne HendricksMathias HumbertGregory S. JohnsonApu KapadiaQiuhong KeMargret KeuperAnna KhorevaKatharina KrombholzLaura Leal-TaixeAles LeonardisEvgeny LevinkovWenbin LiMax LoschLiqian MaMateusz MalinowskiMaxim MaximovDaniel McculleyAshkan MokarianFrank MuecklichSabine MüllerChuong NguyenSeong Joon OhTribhuvanesh OrekondyGerard Pons-MollKonstantinos RematasTobias RitschelMarcus RohrbachAhmed SalemHosnieh SattarJonas ScheerBernt SchieleBernt SchieleDominique SchroederJulia SeiterRijurekha SenAbhishek SharmaIaroslav ShcherbatyiRakshith ShettyMark SimkinHyun Oh SongSreyasi Nag Chowdhury, Mateusz Malinowski, Andreas Bulling, Mario FritzChristoph-Nikolas StraehleYusuke SuganoQianru SunAyush TewariChristian TheobaltEdgar TretschkGerhard TroesterTinne TuytelaarsMisha WagnerTongtong WuWeipeng XuNing YuXucong ZhangYang Zhang All users Mario Fritz

Show all

2019
Journal Articles
	Seong Joon Oh; Rodrigo Benenson; Mario Fritz; Bernt Schiele Person Recognition in Personal Photo Collections Journal Article IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019. Links | BibTeX | Tags: 2019 @article{oh20tpami, title = { Person Recognition in Personal Photo Collections }, author = {Seong Joon Oh and Rodrigo Benenson and Mario Fritz and Bernt Schiele}, url = {https://ieeexplore.ieee.org/document/8519337?source=authoralert}, year = {2019}, date = {2019-11-01}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)}, keywords = {2019}, pubstate = {published}, tppubtype = {article} } Close https://ieeexplore.ieee.org/document/8519337?source=authoralert Close
	Xucong Zhang; Yusuke Sugano; Mario Fritz; Andreas Bulling MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation Journal Article 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}, 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 Close
Incollections
	Seong Joon Oh; Bernt Schiele; Mario Fritz Towards reverse-engineering black-box neural networks Incollection Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 2019. Links | BibTeX | Tags: 2019 @incollection{oh20xai, title = {Towards reverse-engineering black-box neural networks}, author = {Seong Joon Oh and Bernt Schiele and Mario Fritz}, url = {https://link.springer.com/chapter/10.1007/978-3-030-28954-6_7}, year = {2019}, date = {2019-09-10}, booktitle = {Explainable AI: Interpreting, Explaining and Visualizing Deep Learning}, keywords = {2019}, pubstate = {published}, tppubtype = {incollection} } Close https://link.springer.com/chapter/10.1007/978-3-030-28954-6_7 Close
Inproceedings
	Ning Yu; Larry Davis; Mario Fritz Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints Inproceedings International Conference on Computer Vision (ICCV), 2019. Links | BibTeX | Tags: 2019 @inproceedings{yu19iccv, title = {Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints}, author = {Ning Yu and Larry Davis and Mario Fritz}, url = {//arxiv.org/abs/1811.08180 //arxiv.org/pdf/1811.08180.pdf }, year = {2019}, date = {2019-10-30}, booktitle = {International Conference on Computer Vision (ICCV)}, keywords = {2019}, pubstate = {published}, tppubtype = {inproceedings} } Close //arxiv.org/abs/1811.08180 //arxiv.org/pdf/1811.08180.pdf Close
	Maxim Maximov; Tobias Ritschel; Laura Leal-Taixe; Mario Fritz Deep Appearance Maps Inproceedings International Conference on Computer Vision (ICCV), 2019. Links | BibTeX | Tags: 2019 @inproceedings{maximov19iccv, title = {Deep Appearance Maps}, author = {Maxim Maximov and Tobias Ritschel and Laura Leal-Taixe and Mario Fritz}, url = {//arxiv.org/abs/1804.00863 //arxiv.org/pdf/1804.00863.pdf}, year = {2019}, date = {2019-10-29}, booktitle = {International Conference on Computer Vision (ICCV)}, keywords = {2019}, pubstate = {published}, tppubtype = {inproceedings} } Close //arxiv.org/abs/1804.00863 //arxiv.org/pdf/1804.00863.pdf Close
	Tribhuvanesh Orekondy; Bernt Schiele; Mario Fritz Knockoff Nets: Stealing Functionality of Black-Box Models Inproceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. Links | BibTeX | Tags: 2019 @inproceedings{orekondy19cvpr, title = {Knockoff Nets: Stealing Functionality of Black-Box Models }, author = {Tribhuvanesh Orekondy and Bernt Schiele and Mario Fritz}, url = {preliminary version: https://arxiv.org/abs/1812.02766 https://arxiv.org/pdf/1812.02766}, year = {2019}, date = {2019-06-18}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, keywords = {2019}, pubstate = {published}, tppubtype = {inproceedings} } Close preliminary version: https://arxiv.org/abs/1812.02766 https://arxiv.org/pdf/1812.02766 Close
	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 Inproceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. Links | BibTeX | Tags: 2019 @inproceedings{shetty19cvpr, 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 = {preliminary version: https://arxiv.org/abs/1812.06707 https://arxiv.org/pdf/1812.06707.pdf}, year = {2019}, date = {2019-06-17}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, keywords = {2019}, pubstate = {published}, tppubtype = {inproceedings} } Close preliminary version: https://arxiv.org/abs/1812.06707 https://arxiv.org/pdf/1812.06707.pdf Close
	Qiuhong Ke; Mario Fritz; Bernt Schiele Time-Conditioned Action Anticipation in One Shot Inproceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. BibTeX | Tags: 2019 @inproceedings{ke19cvpr, title = {Time-Conditioned Action Anticipation in One Shot}, author = {Qiuhong Ke and Mario Fritz and Bernt Schiele}, year = {2019}, date = {2019-06-16}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, keywords = {2019}, pubstate = {published}, tppubtype = {inproceedings} } Close
	Apratim Bhattacharyya; Mario Fritz; Bernt Schiele Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods Inproceedings International Conference on Representation Learning (ICLR), 2019. Links | BibTeX | Tags: 2019 @inproceedings{apratim19iclr, title = {Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods}, author = {Apratim Bhattacharyya and Mario Fritz and Bernt Schiele}, url = {https://arxiv.org/abs/1810.00746 https://arxiv.org/pdf/1810.00746.pdf}, year = {2019}, date = {2019-05-06}, booktitle = {International Conference on Representation Learning (ICLR)}, keywords = {2019}, pubstate = {published}, tppubtype = {inproceedings} } Close https://arxiv.org/abs/1810.00746 https://arxiv.org/pdf/1810.00746.pdf Close
	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 Inproceedings Annual Network and Distributed System Security Symposium (NDSS), 2019, (to appear). Links | BibTeX | Tags: 2019 @inproceedings{ndss19salem, 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 = {preliminary: https://arxiv.org/abs/1806.01246 https://arxiv.org/pdf/1806.01246.pdf }, year = {2019}, date = {2019-02-24}, booktitle = {Annual Network and Distributed System Security Symposium (NDSS)}, note = {to appear}, keywords = {2019}, pubstate = {published}, tppubtype = {inproceedings} } Close preliminary: https://arxiv.org/abs/1806.01246 https://arxiv.org/pdf/1806.01246.pdf Close
	Hosnieh Sattar; Gerard Pons-Moll; Mario Fritz Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources Inproceedings IEEE Winter Conference on Applications of Computer Vision (WACV), 2019, (to appear). Links | BibTeX | Tags: 2019 @inproceedings{sattar19wacv, 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 = {preliminary: //arxiv.org/abs/1807.03235 //arxiv.org/pdf/1807.03235.pdf}, year = {2019}, date = {2019-01-08}, booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)}, note = {to appear}, keywords = {2019}, pubstate = {published}, tppubtype = {inproceedings} } Close preliminary: //arxiv.org/abs/1807.03235 //arxiv.org/pdf/1807.03235.pdf Close
Technical Reports
	Apratim Bhattacharyya; Mario Fritz; Bernt Schiele "Best-of-Many-Samples" Distribution Matching Technical Report arXiv:1909.12598, 2019. Links | BibTeX | Tags: 2019 @techreport{bhattacharyya19arxivb, title = {"Best-of-Many-Samples" Distribution Matching}, author = {Apratim Bhattacharyya and Mario Fritz and Bernt Schiele}, url = {//arxiv.org/abs/1909.12598 //arxiv.org/pdf/1909.12598.pdf}, year = {2019}, date = {2019-09-27}, type = {arXiv:1909.12598}, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close //arxiv.org/abs/1909.12598 //arxiv.org/pdf/1909.12598.pdf Close
	Dingfan Chen; Ning Yu; Yang Zhang; Mario Fritz GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs Technical Report arXiv:1909.03935, 2019. Links | BibTeX | Tags: 2019 @techreport{chen19arxiv, title = {GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs}, author = {Dingfan Chen and Ning Yu and Yang Zhang and Mario Fritz}, url = {https://arxiv.org/abs/1909.03935 https://arxiv.org/pdf/1909.03935.pdf}, year = {2019}, date = {2019-09-09}, type = {arXiv:1909.03935}, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close https://arxiv.org/abs/1909.03935 https://arxiv.org/pdf/1909.03935.pdf Close
	Sahar Abdelnabi; Katharina Krombholz; Mario Fritz WhiteNet: Phishing Website Detection by Visual Whitelists Technical Report arXiv:1909.00300, 2019. Links | BibTeX | Tags: 2019 @techreport{abdelnabi19arxiv, title = {WhiteNet: Phishing Website Detection by Visual Whitelists}, author = {Sahar Abdelnabi and Katharina Krombholz and Mario Fritz}, url = {https://arxiv.org/abs/1909.00300 https://arxiv.org/pdf/1909.00300.pdf}, year = {2019}, date = {2019-09-01}, type = {arXiv:1909.00300}, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close https://arxiv.org/abs/1909.00300 https://arxiv.org/pdf/1909.00300.pdf Close
	Apratim Bhattacharyya; Michael Hanselmann; Mario Fritz; Bernt Schiele; Christoph-Nikolas Straehle Conditional Flow Variational Autoencoders for Structured Sequence Prediction Technical Report arXiv:1908.09008, 2019. Links | BibTeX | Tags: 2019 @techreport{bhattacharyya19arxiv, title = {Conditional Flow Variational Autoencoders for Structured Sequence Prediction}, author = {Apratim Bhattacharyya and Michael Hanselmann and Mario Fritz and Bernt Schiele and Christoph-Nikolas Straehle}, url = {https://arxiv.org/abs/1908.09008 https://arxiv.org/pdf/1908.09008.pdf}, year = {2019}, date = {2019-08-24}, type = {arXiv:1908.09008}, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close https://arxiv.org/abs/1908.09008 https://arxiv.org/pdf/1908.09008.pdf Close
	Max Losch; Mario Fritz; Bernt Schiele Interpretability Beyond Classification Output: Semantic Bottleneck Networks Technical Report arXiv:1907.10882 , 2019. Links | BibTeX | Tags: 2019 @techreport{losch19arxiv, title = {Interpretability Beyond Classification Output: Semantic Bottleneck Networks}, author = {Max Losch and Mario Fritz and Bernt Schiele}, url = {//arxiv.org/abs/1907.10882 //arxiv.org/pdf/1907.10882.pdf}, year = {2019}, date = {2019-07-25}, type = {arXiv:1907.10882 }, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close //arxiv.org/abs/1907.10882 //arxiv.org/pdf/1907.10882.pdf Close
	Tribhuvanesh Orekondy; Bernt Schiele; Mario Fritz Prediction Poisoning: Utility-Constrained Defenses Against Model Stealing Attacks Technical Report arXiv:1906.10908 , 2019. Links | BibTeX | Tags: 2019 @techreport{orekondy19arxiv, title = {Prediction Poisoning: Utility-Constrained Defenses Against Model Stealing Attacks}, author = {Tribhuvanesh Orekondy and Bernt Schiele and Mario Fritz}, url = {https://arxiv.org/abs/1906.10908 https://arxiv.org/pdf/1906.10908.pdf}, year = {2019}, date = {2019-06-26}, type = {arXiv:1906.10908 }, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close https://arxiv.org/abs/1906.10908 https://arxiv.org/pdf/1906.10908.pdf Close
	Hossein Hajipour; Apratim Bhattacharya; Mario Fritz SampleFix: Learning to Correct Programs by Sampling Diverse Fixes Technical Report arXiv:1906.10502, 2019. Links | BibTeX | Tags: 2019 @techreport{hajipour19arxiv, title = {SampleFix: Learning to Correct Programs by Sampling Diverse Fixes}, author = {Hossein Hajipour and Apratim Bhattacharya and Mario Fritz}, url = {//arxiv.org/abs/1906.10502 //arxiv.org/pdf/1906.10502.pdf}, year = {2019}, date = {2019-06-24}, type = {arXiv:1906.10502}, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close //arxiv.org/abs/1906.10502 //arxiv.org/pdf/1906.10502.pdf Close
	Hosnieh Sattar; Katharina Krombholz; Gerard Pons-Moll; Mario Fritz Shape Evasion: Preventing Body Shape Inference of Multi-Stage Approaches Technical Report arXiv:1905.11503 , 2019. Links | BibTeX | Tags: 2019 @techreport{sattar19arxiv, title = {Shape Evasion: Preventing Body Shape Inference of Multi-Stage Approaches}, author = {Hosnieh Sattar and Katharina Krombholz and Gerard Pons-Moll and Mario Fritz}, url = {//arxiv.org/abs/1905.11503 //arxiv.org/pdf/1905.11503.pdf}, year = {2019}, date = {2019-05-30}, type = {arXiv:1905.11503 }, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close //arxiv.org/abs/1905.11503 //arxiv.org/pdf/1905.11503.pdf Close
	Wenbin Li; Ales Leonardis; Jeannette Bohg; Mario Fritz Learning Manipulation under Physics Constraints with Visual Perception Technical Report 2019. Links | BibTeX | Tags: 2019 @techreport{li19arxiv, title = {Learning Manipulation under Physics Constraints with Visual Perception}, author = {Wenbin Li and Ales Leonardis and Jeannette Bohg and Mario Fritz}, url = {//arxiv.org/abs/1904.09860 //arxiv.org/pdf/1904.09860.pdf }, year = {2019}, date = {2019-04-19}, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close //arxiv.org/abs/1904.09860 //arxiv.org/pdf/1904.09860.pdf Close
	Ahmed Salem; Apratim Bhattacharya; Michael Backes; Mario Fritz; Yang Zhang Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning Technical Report 2019. Links | BibTeX | Tags: 2019 @techreport{salem19arxiv, title = {Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning}, author = {Ahmed Salem and Apratim Bhattacharya and Michael Backes and Mario Fritz and Yang Zhang}, url = {//arxiv.org/abs/1904.01067 //arxiv.org/pdf/1904.01067.pdf}, year = {2019}, date = {2019-04-03}, journal = {arXiv:1904.01067}, keywords = {2019}, pubstate = {published}, tppubtype = {techreport} } Close //arxiv.org/abs/1904.01067 //arxiv.org/pdf/1904.01067.pdf Close
Workshops
	Ahmed Salem; Apratim Bhattacharya; Michael Backes; Mario Fritz; Yang Zhang Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning Workshop Hot Topics in Privacy Enhancing Technologies (HotPETs), 2019. Links | BibTeX | Tags: 2019 @workshop{salem19hotpet, title = {Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning}, author = {Ahmed Salem and Apratim Bhattacharya and Michael Backes and Mario Fritz and Yang Zhang}, url = {https://arxiv.org/abs/1904.01067 https://arxiv.org/pdf/1904.01067.pdf}, year = {2019}, date = {2019-07-19}, booktitle = {Hot Topics in Privacy Enhancing Technologies (HotPETs)}, keywords = {2019}, pubstate = {published}, tppubtype = {workshop} } Close https://arxiv.org/abs/1904.01067 https://arxiv.org/pdf/1904.01067.pdf Close
	Rakibul Hasan; David Crandall; Mario Fritz; Apu Kapadia Understanding and Recognizing Bystanders in Images for Privacy Protection Workshop Privacy, Usability, and Transparency (PUT) @ PETs, 2019. Links | BibTeX | Tags: 2019 @workshop{hasan19put, title = {Understanding and Recognizing Bystanders in Images for Privacy Protection}, author = {Rakibul Hasan and David Crandall and Mario Fritz and Apu Kapadia}, url = {https://petsymposium.org/2019/files/workshop/abstracts/PUT_2019_paper_15.pdf}, year = {2019}, date = {2019-07-15}, booktitle = {Privacy, Usability, and Transparency (PUT) @ PETs}, keywords = {2019}, pubstate = {published}, tppubtype = {workshop} } Close https://petsymposium.org/2019/files/workshop/abstracts/PUT_2019_paper_15.pdf Close
2018
Technical Reports
	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: 2019 @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 = {2019}, pubstate = {published}, tppubtype = {techreport} } Close https://arxiv.org/abs/1812.06707 https://arxiv.org/pdf/1812.06707.pdf Close

Imprint Data Protection