| ESIM: an open event camera simulator H Rebecq, D Gehrig, D Scaramuzza Conference on robot learning, 969-982, 2018 | 223 | 2018 |
| End-to-end learning of representations for asynchronous event-based data D Gehrig, A Loquercio, KG Derpanis, D Scaramuzza Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 168 | 2019 |
| Asynchronous, Photometric Feature Tracking using Events and Frames D Gehrig Robotics and Perception Group, University of Zurich, 2018 | 102 | 2018 |
| Asynchronous, photometric feature tracking using events and frames D Gehrig, H Rebecq, G Gallego, D Scaramuzza Proceedings of the European Conference on Computer Vision (ECCV), 750-765, 2018 | 102 | 2018 |
| Video to events: Recycling video datasets for event cameras D Gehrig, M Gehrig, J Hidalgo-Carrió, D Scaramuzza Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 96 | 2020 |
| EKLT: Asynchronous photometric feature tracking using events and frames D Gehrig, H Rebecq, G Gallego, D Scaramuzza International Journal of Computer Vision 128 (3), 601-618, 2020 | 93 | 2020 |
| Fast image reconstruction with an event camera C Scheerlinck, H Rebecq, D Gehrig, N Barnes, R Mahony, D Scaramuzza Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020 | 90 | 2020 |
| Dsec: A stereo event camera dataset for driving scenarios M Gehrig, W Aarents, D Gehrig, D Scaramuzza IEEE Robotics and Automation Letters 6 (3), 4947-4954, 2021 | 70 | 2021 |
| Event-based Asynchronous Sparse Convolutional Networks N Messikommer*, D Gehrig*, A Loquercio, D Scaramuzza Proceedings of the European Conference on Computer Vision (ECCV), 2020 | 62 | 2020 |
| Learning Monocular Dense Depth from Events J Hidalgo-Carrió, D Gehrig, D Scaramuzza International Conference on 3D Vision (3DV), 2020 | 46 | 2020 |
| Time Lens: Event-based Video Frame Interpolation S Tulyakov*, D Gehrig*, S Georgoulis, J Erbach, M Gehrig, Y Li, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 44 | 2021 |
| Combining events and frames using recurrent asynchronous multimodal networks for monocular depth prediction D Gehrig, M Rüegg, M Gehrig, J Hidalgo-Carrió, D Scaramuzza IEEE Robotics and Automation Letters 6 (2), 2822-2829, 2021 | 42 | 2021 |
| E-raft: Dense optical flow from event cameras M Gehrig, M Millhäusler, D Gehrig, D Scaramuzza 2021 International Conference on 3D Vision (3DV), 197-206, 2021 | 33* | 2021 |
| How to calibrate your event camera M Muglikar, M Gehrig, D Gehrig, D Scaramuzza Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 13 | 2021 |
| Bridging the gap between events and frames through unsupervised domain adaptation N Messikommer, D Gehrig, M Gehrig, D Scaramuzza IEEE Robotics and Automation Letters 7 (2), 3515-3522, 2022 | 10 | 2022 |
| Time Lens++: Event-based Frame Interpolation with Parametric Non-linear Flow and Multi-scale Fusion S Tulyakov, A Bochicchio, D Gehrig, S Georgoulis, Y Li, D Scaramuzza Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 10 | 2022 |
| AEGNN: Asynchronous Event-based Graph Neural Networks S Schaefer, D Gehrig, D Scaramuzza Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 9 | 2022 |
| Ess: Learning event-based semantic segmentation from still images Z Sun, N Messikommer, D Gehrig, D Scaramuzza Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 4 | 2022 |
| Exploring Event Camera-based Odometry for Planetary Robots F Mahlknecht, D Gehrig, J Nash, FM Rockenbauer, B Morrell, J Delaune, ... IEEE Robotics and Automation Letters, 2022 | 4 | 2022 |
| Multi-bracket high dynamic range imaging with event cameras N Messikommer, S Georgoulis, D Gehrig, S Tulyakov, J Erbach, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 3 | 2022 |
Davide ScaramuzzaProfessor of Robotics and Perception, University of ZurichПотвърден имейл адрес: ifi.uzh.ch
