| Phase-based frame interpolation for video S Meyer, O Wang, H Zimmer, M Grosse, A Sorkine-Hornung Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 339 | 2015 |
| PhaseNet for Video Frame Interpolation S Meyer, A Djelouah, B McWilliams, A Sorkine-Hornung, M Gross, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 209 | 2018 |
| Neural inter-frame compression for video coding A Djelouah, J Campos, S Schaub-Meyer, C Schroers Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 196 | 2019 |
| Deep video color propagation S Meyer, V Cornillčre, A Djelouah, C Schroers, M Gross British Machine Vision Conference, 2018 | 56 | 2018 |
| Fast axiomatic attribution for neural networks R Hesse, S Schaub-Meyer, S Roth Advances in Neural Information Processing Systems 34, 19513-19524, 2021 | 33 | 2021 |
| Dense unsupervised learning for video segmentation N Araslanov, S Schaub-Meyer, S Roth Advances in Neural Information Processing Systems 34, 25308-25319, 2021 | 32 | 2021 |
| Phase-Based Modification Transfer for Video S Meyer, A Sorkine-Hornung, M Gross European Conference on Computer Vision, 633-648, 2016 | 22 | 2016 |
| FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods R Hesse, S Schaub-Meyer, S Roth Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 16 | 2023 |
| Content-Adaptive Downsampling in Convolutional Neural Networks R Hesse, S Schaub-Meyer, S Roth Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
| Video frame interpolation using a convolutional neural network C Schroers, S Meyer, A Djelouah, AS Hornung, B McWilliams, M Gross US Patent 10,491,856, 2019 | 6 | 2019 |
| Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images K Singh, T Navaratnam, J Holmer, S Schaub-Meyer, S Roth Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 5 | 2024 |
| Style Transfer for Keypoint Matching Under Adverse Conditions A Uzpak, A Djelouah, S Schaub-Meyer 2020 International Conference on 3D Vision (3DV), 1089-1097, 2020 | 5 | 2020 |
| Systems and methods for interpolating frames of a video H Zimmer, AS Hornung, S Meyer, M Grosse, O Wang US Patent 9,571,786, 2017 | 5 | 2017 |
| Machine learning based video compression C Schroers, S Schaub, E Doggett, J Mcphillen, S Labrozzi, A Djelouah US Patent App. 16/261,441, 2020 | 4 | 2020 |
| Efficient Feature Extraction for High-resolution Video Frame Interpolation M Nottebaum, S Roth, S Schaub-Meyer British Machine Vision Conference, 2022 | 3 | 2022 |
| Simplifying the Process of Creating Augmented Outdoor Scenes R Chalumattu, S Schaub-Meyer, R Wiethuchter, S Klingler, M Gross 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 1-6, 2020 | 3 | 2020 |
| NeurIPS’22 Cross-Domain MetaDL Challenge: Results and lessons learned D Carrión-Ojeda, M Alam, S Escalera, A Farahat, D Ghosh, TG Diaz, ... NeurIPS 2022 Competition Track, 50-72, 2023 | 2 | 2023 |
| Systems and methods for propagating edits through a video AS Hornung, S Meyer US Patent 9,911,215, 2018 | 2 | 2018 |
| Benchmarking Video Frame Interpolation S Kiefhaber, S Niklaus, F Liu, S Schaub-Meyer arXiv preprint arXiv:2403.17128, 2024 | 1 | 2024 |
| MACHINE LEARNING BASED VIDEO COMPRESSION C Schroers, S Schaub, E Doggett, J Mcphillen, S Labrozzi, A Djelouah US Patent App. 18/049,262, 2023 | 1 | 2023 |
Abdelaziz DjelouahDisney ResearchVerified email at disneyresearch.com
