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) - 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, attribution, watermarking and responsible disclosure:
- ArXiv’21: 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:
- 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
- NeurIPS’20: GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators
- NeurIPS-W’20: SampleFix: Learning to Correct Programs by Sampling Diverse Fixes
- NeurIPS-W’20: IReEn: Iterative Reverse-Engineering of Black-Box Functions via Neural Program Synthesis
- NeurIPS-W’20: Haar Wavelet based Block Autoregressive Flows for Trajectories
- CCS’20: VisualPhishNet: Zero-Day Phishing Website Detection by Visual Similarity
- CCS’20: GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs
- S&P’20: Automatically Detecting Bystanders in Photos to Reduce Privacy Risks
- USENIX Security’20: Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning
- ICLR’20: Prediction Poisoning: Utility-Constrained Defenses Against Model Stealing Attacks
- CVPR’20: Towards Causal VQA: Revealing and Reducing Spurious Correlations by Invariant and Covariant Semantic Editing
- CVPR’20: Normalizing Flows with Multi-scale Autoregressive Priors
- ECCV’20: Towards Automated Testing and Robustification by Semantic Adversarial Data Generation
- ECCV’20: Inclusive GAN: Improving Data and Minority Coverage in Generative Models
- ECCV’20: Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation
- ECCV-W’20: Body Shape Privacy in Images: Understanding Privacy and Preventing Automatic Shape Extraction
- ECCV-W’20: Synthetic Convolutional Features for Improved Semantic Segmentation
- NEUCOM’20: Deep gaze pooling: Inferring and visually decoding search intents from human gaze fixations
- GCPR’20: Semantic Bottlenecks: Quantifying & Improving Inspectability of Deep Representations
- GCPR’20: Long-Tailed Recognition Using Class-Balanced Experts
- GCPR’20: Haar Wavelet based Block Autoregressive Flows for Trajectories
- TPAMI’20: Person Recognition in Personal Photo Collections
- Explainable AI Book: Towards reverse-engineering black-box neural networks
Most recent work on ArXiv:
- ArXiv’21: Backdoor Attacks on Network Certification via Data Poisoning
- ArXiv’21: ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
- ArXiv’21: Responsible Disclosure of Generative Models Using Scalable Fingerprinting
- ArXiv’20: CosSGD: Nonlinear Quantization for Communication-efficient Federated Learning
News, talks, events:
- Recent program committees: ICML’21, NeurIPS’22, S&P’22, EuroS&P’22, CVPR’22 (AC)
- 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)
2017 |
|
Journal Articles |
|
 | Novel Views of Objects from a Single Image Journal Article Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017. |
2016 |
|
Inproceedings |
|
 | Faceless Person Recognition; Privacy Implications in Social Media Inproceedings European Conference on Computer Vision (ECCV), 2016, (to appear). |
 | VConv-DAE: Deep Volumetric Shape Learning Without Object Labels Inproceedings Geometry Meets Deep Learning Workshop at European Conference on Computer Vision (ECCV-W), 2016. |
 | Towards Segmenting Consumer Stereo Videos: Benchmark, Baselines and Ensembles Inproceedings Asian Conference on Computer Vision (ACCV), 2016, (to appear). |
 | Mean Box Pooling: A Rich Image Representation and Output Embedding for the Visual Madlibs Task Inproceedings British Machine Vision Conference (BMVC), 2016, (to appear). |
 | Deep Reflectance Maps Inproceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. |
 | Multi-Cue Zero-Shot Learning with Strong Supervision Inproceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. |
 | I-Pic: A Platform for Privacy-Compliant Image Capture Inproceedings The 14th International Conference on Mobile Systems, Applications, and Services (MobiSys'16), Singapore, 2016. |
 | Learning to Select Long Track Features for Structure-From-Motion & Visual SLAM Inproceedings German Conference on Pattern Recognition (GCPR), 2016. |
 | Contextual Media Retrieval Using Natural Language Queries Inproceedings ACM International Conference on Multimedia Retrieval (ICMR), 2016, (to appear). |
 | Recognition of Ongoing Complex Activities by Sequence Prediction over a Hierarchical Label Space Inproceedings IEEE Winter Conference on Applications of Computer Vision (WACV), 2016. |
Miscellaneous |
|
 | Visual Stability Prediction and Its Application to Manipulation Miscellaneous NIPS Workshop on Intuitive Physics, 2016. |
 | Long Term Boundary Extrapolation for Deterministic Motion Miscellaneous NIPS Workshop on Intuitive Physics, 2016. |
 | Faceless Person Recognition; Privacy Implications in Social Media Miscellaneous 4th Workshop on Web-scale Vision and Social Media (VSM), ECCV'16, 2016. |
 | Ask Your Neurons Again: Analysis of Deep Methods with Global Image Representation Miscellaneous VQA Challenge Workshop at CVPR, 2016. |
PhD Theses |
|
 | Bayesian Non-Parametrics for Multi-Modal Segmentation PhD Thesis 2016. |
Technical Reports |
|
 | Predicting the Category and Attributes of Visual Search Targets Using Deep Gaze Pooling Technical Report arXiv:1611.10162 [cs.CV], 2016. |
 | Long-Term Image Boundary Extrapolation Technical Report arXiv:1611.08841 [cs.CV], 2016. |
 | Natural Illumination from Multiple Materials Using Deep Learning Technical Report arXiv:1611.09325 [cs.CV], 2016. |
 | It's Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation Technical Report arXiv:1611.08860 [cs.CV], 2016. |
 | Tutorial on Answering Questions about Images with Deep Learning Technical Report arXiv:1610.01076 [cs.CV], 2016, (Tutorial given at 2nd Summer School on Integrating Vision and Language: Deep Learning). |
| Visual Stability Prediction and Its Application to Manipulation Technical Report arXiv:1609.04861 [cs.CV], 2016. |
 | Spatio-Temporal Image Boundary Extrapolation Technical Report arXiv:1605.07363 [cs.CV], 2016. |
 | Ask Your Neurons: A Deep Learning Approach to Visual Question Answering Technical Report arXiv:1605.02697 [cs.CV], 2016. |
 | VConv-DAE: Deep Volumetric Shape Learning Without Object Labels Technical Report arXiv:1604.03755 [cs.CV], 2016. |
 | RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling Technical Report arXiv:1604.02388 [cs.CV], 2016. |
 | To Fall Or Not To Fall: A Visual Approach to Physical Stability Prediction Technical Report arXiv:1604.00066 [cs.CV], 2016. |
 | DeLight-Net: Decomposing Reflectance Maps into Specular Materials and Natural Illumination Technical Report arXiv:1602.00328 [cs.CV], 2016. |
| Multi-Cue Zero-Shot Learning with Strong Supervision Technical Report arXiv:1603.08754 [cs.CV], 2016. |
| Novel Views of Objects from a Single Image Technical Report arXiv:1602.00328 [cs.CV], 2016. |
| Contextual Media Retrieval Using Natural Language Queries Technical Report arXiv:1602.04983 [cs.IR], 2016. |