| Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints N Yu, L Davis, M Fritz IEEE International Conference on Computer Vision (ICCV), 2019 | 558 | 2019 |
| Gan-leaks: A taxonomy of membership inference attacks against generative models D Chen, N Yu, Y Zhang, M Fritz ACM SIGSAC Conference on Computer and Communications Security (CCS), 2020 | 433 | 2020 |
| Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data N Yu, V Skripniuk, S Abdelnabi, M Fritz IEEE International Conference on Computer Vision (ICCV), 2021 | 239 | 2021 |
| DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Diffusion Models Z Sha, Z Li, N Yu, Y Zhang ACM SIGSAC Conference on Computer and Communications Security (CCS), 2023 | 148* | 2023 |
| Responsible disclosure of generative models using scalable fingerprinting N Yu, V Skripniuk, D Chen, L Davis, M Fritz International Conference on Learning Representations (ICLR), 2022 | 101 | 2022 |
| UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild C Qin, S Zhang, N Yu, Y Feng, X Yang, Y Zhou, H Wang, JC Niebles, ... Conference on Neural Information Processing Systems (NeurIPS), 2023 | 98 | 2023 |
| ULIP-2: Towards Scalable Multimodal Pre-training For 3D Understanding L Xue, N Yu, S Zhang, J Li, R Martín-Martín, J Wu, C Xiong, R Xu, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 | 94 | 2024 |
| HIVE: Harnessing Human Feedback for Instructional Visual Editing S Zhang, X Yang, Y Feng, C Qin, CC Chen, N Yu, Z Chen, H Wang, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 | 90 | 2024 |
| Dual contrastive loss and attention for gans N Yu, G Liu, A Dundar, A Tao, B Catanzaro, L Davis, M Fritz IEEE International Conference on Computer Vision (ICCV), 2021 | 70 | 2021 |
| Inclusive GAN: Improving Data and Minority Coverage in Generative Models N Yu, K Li, P Zhou, J Malik, L Davis, M Fritz European Conference on Computer Vision (ECCV), 2020 | 70 | 2020 |
| Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis Y He, N Yu, M Keuper, M Fritz International Joint Conference on Artificial Intelligence (IJCAI), 2021 | 69 | 2021 |
| Membership inference attacks against text-to-image generation models Y Wu, N Yu, Z Li, M Backes, Y Zhang | 64 | 2022 |
| Keys to Better Image Inpainting: Structure and Texture Go Hand in Hand J Jain, Y Zhou, N Yu, H Shi IEEE Winter Conference on Applications of Computer Vision (WACV), 2023 | 59 | 2023 |
| RelaxLoss: Defending Membership Inference Attacks without Losing Utility D Chen, N Yu, M Fritz International Conference on Learning Representations (ICLR), 2022 | 52 | 2022 |
| Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture N Yu, C Barnes, E Shechtman, S Amirghodsi, M Lukac IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 52 | 2019 |
| RoSteALS: Robust Steganography using Autoencoder Latent Space T Bui, S Agarwal, N Yu, J Collomosse CVPR Workshop on Media Forensics, 2023 | 47 | 2023 |
| Application of deep learning for image-based Chinese market food nutrients estimation P Ma, CP Lau, N Yu, A Li, J Sheng Food Chemistry 373, 130994, 2022 | 46 | 2022 |
| Image-based Nutrient Estimation for Chinese Dishes Using Deep Learning P Ma, CP Lau, N Yu, A Li, P Liu, Q Wang, J Sheng Food Research International, 2021 | 41 | 2021 |
| xgen-mm (blip-3): A family of open large multimodal models L Xue, M Shu, A Awadalla, J Wang, A Yan, S Purushwalkam, H Zhou, ... arXiv preprint arXiv:2408.08872, 2024 | 40 | 2024 |
| Application of machine learning for estimating label nutrients using USDA Global Branded Food Products Database,(BFPD) P Ma, A Li, N Yu, Y Li, R Bahadur, Q Wang, JK Ahuja Journal of Food Composition and Analysis, 2021 | 38 | 2021 |
Mario FritzFaculty CISPA Helmholtz Center for Information Security; Professor Saarland UniversityVerified email at cispa.de
