| High‐resolution neural face swapping for visual effects J Naruniec, L Helminger, C Schroers, RM Weber Computer Graphics Forum 39 (4), 173-184, 2020 | 118 | 2020 |
| Are Wet-Induced Wrinkled Fingers Primate Rain Treads? M Changizi, R Weber, R Kotecha, J Palazzo Brain, Behavior and Evolution 77 (4), 286-290, 2011 | 61 | 2011 |
| CADS: Unleashing the diversity of diffusion models through condition-annealed sampling S Sadat, J Buhmann, D Bradley, O Hilliges, RM Weber arXiv preprint arXiv:2310.17347, 2023 | 36 | 2023 |
| Telemetry anomaly detection system using machine learning to streamline mission operations MM Fernández, Y Yue, R Weber 2017 6th International Conference on Space Mission Challenges for …, 2017 | 25 | 2017 |
| Controllable inversion of black-box face recognition models via diffusion M Kansy, A Raël, G Mignone, J Naruniec, C Schroers, M Gross, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 19 | 2023 |
| Unsupervised deep representations for learning audience facial behaviors S Saha, R Navarathna, L Helminger, RM Weber Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 16 | 2018 |
| Three-dimensional geometry-based models for changing facial identities in video frames and images JK Naruniec, DE Bradley, T Etterlin, PFU Gotardo, LM Helminger, ... US Patent 11,222,466, 2022 | 15 | 2022 |
| Automated image synthesis using a comb neural network architecture J Naruniec, R Weber, C Schroers US Patent 10,902,571, 2021 | 15 | 2021 |
| Spectrogram feature losses for music source separation A Sahai, R Weber, B McWilliams 2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019 | 14 | 2019 |
| Deep adaptive sampling and reconstruction using analytic distributions F Salehi, M Manzi, G Roethlin, R Weber, C Schroers, M Papas ACM Transactions on Graphics (TOG) 41 (6), 1-16, 2022 | 9 | 2022 |
| Tunable models for changing faces in images LM Helminger, JK Naruniec, RM Weber, CR Schroers US Patent 11,568,524, 2023 | 8 | 2023 |
| Audio feature extraction with convolutional neural autoencoders with application to voice conversion G Elhami, RM Weber | 8 | 2019 |
| InspireMe: learning sequence models for stories V Fortuin, R Weber, S Schriber, D Wotruba, M Gross Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 8 | 2018 |
| Litevae: Lightweight and efficient variational autoencoders for latent diffusion models S Sadat, J Buhmann, D Bradley, O Hilliges, RM Weber arXiv preprint arXiv:2405.14477, 2024 | 7 | 2024 |
| Decision-tree analysis of control strategies RM Weber, BR Fajen Psychonomic Bulletin & Review 22, 653-672, 2015 | 6 | 2015 |
| Learning dynamic 3D geometry and texture for video face swapping C Otto, J Naruniec, L Helminger, T Etterlin, G Mignone, P Chandran, ... Computer Graphics Forum 41 (7), 611-622, 2022 | 5 | 2022 |
| Systems and methods for image compression at multiple, different bitrates C Schroers, E Doggett, SM Mandt, J Mcphillen, S Labrozzi, R Weber, ... US Patent 11,335,034, 2022 | 5 | 2022 |
| No training, no problem: Rethinking classifier-free guidance for diffusion models S Sadat, M Kansy, O Hilliges, RM Weber arXiv preprint arXiv:2407.02687, 2024 | 4 | 2024 |
| Eliminating oversaturation and artifacts of high guidance scales in diffusion models S Sadat, O Hilliges, RM Weber The Thirteenth International Conference on Learning Representations, 2024 | 2 | 2024 |
| Characterizing audience engagement based on emotional alignment with characters RM Weber, G Mignone, JK Naruniec, AM Baker, F Salehi, D Li US Patent 11,849,179, 2023 | 2 | 2023 |
Christopher SchroersPrincipal Research Scientist, Disney Research|StudiosVerified email at disneyresearch.com
