| Learning human motion models for long-term predictions P Ghosh, J Song, E Aksan, O Hilliges 2017 International Conference on 3D Vision (3DV), 458-466, 2017 | 231 | 2017 |
| Deep inertial poser: Learning to reconstruct human pose from sparse inertial measurements in real time Y Huang, M Kaufmann, E Aksan, MJ Black, O Hilliges, G Pons-Moll ACM Transactions on Graphics (TOG) 37 (6), 1-15, 2018 | 225 | 2018 |
| A spatio-temporal transformer for 3D human motion prediction E Aksan, M Kaufmann, P Cao, O Hilliges 2021 International Conference on 3D Vision (3DV), 2021 | 149* | 2021 |
| Structured prediction helps 3d human motion modelling E Aksan, M Kaufmann, O Hilliges Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 146 | 2019 |
| Deepwriting: Making digital ink editable via deep generative modeling E Aksan, F Pece, O Hilliges Proceedings of the 2018 CHI conference on human factors in computing systems …, 2018 | 71 | 2018 |
| Guiding infogan with semi-supervision A Spurr, E Aksan, O Hilliges Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 62 | 2017 |
| Convolutional autoencoders for human motion infilling M Kaufmann, E Aksan, J Song, F Pece, R Ziegler, O Hilliges 2020 International Conference on 3D Vision (3DV), 918-927, 2020 | 60 | 2020 |
| Stcn: Stochastic temporal convolutional networks E Aksan, O Hilliges International Conference on Learning Representations (ICLR 2019), 2019 | 58 | 2019 |
| Towards end-to-end video-based eye-tracking S Park, E Aksan, X Zhang, O Hilliges European Conference on Computer Vision, 747-763, 2020 | 50 | 2020 |
| D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactions S Christen, M Kocabas, E Aksan, J Hwangbo, J Song, O Hilliges Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2022 | 35 | 2022 |
| Cose: Compositional stroke embeddings E Aksan, T Deselaers, A Tagliasacchi, O Hilliges Advances in Neural Information Processing Systems (NeurIPS) 2020 33, 10041 …, 2020 | 30 | 2020 |
| Learning functionally decomposed hierarchies for continuous control tasks with path planning S Christen, L Jendele, E Aksan, O Hilliges IEEE Robotics and Automation Letters 6 (2), 3623-3630, 2021 | 18 | 2021 |
| The DIDI dataset: digital ink diagram data P Gervais, T Deselaers, E Aksan, O Hilliges arXiv preprint arXiv:2002.09303, 2020 | 12 | 2020 |
| Learning deep temporal representations for fMRI brain decoding O Firat, E Aksan, I Oztekin, FT Yarman Vural Machine Learning Meets Medical Imaging: First International Workshop, MLMMI …, 2015 | 12 | 2015 |
| Reconstructing Action-Conditioned Human-Object Interactions Using Commonsense Knowledge Priors X Wang, G Li, YL Kuo, M Kocabas, E Aksan, O Hilliges 2022 International Conference on 3D Vision (3DV), 2022 | 6 | 2022 |
| Large scale functional connectivity for brain decoding O Firat, I Onal, E Aksan, B Velioglu, I Oztekin, FTY Vural 11 th IASTED International Conference on Biomedical Engineering (BioMed), 2014 | 6 | 2014 |
| Learning deep temporal representations for brain decoding O Firat, E Aksan, I Oztekin, FTY Vural arXiv preprint arXiv:1412.7522, 2014 | 5 | 2014 |
| Modeling the brain connectivity for pattern analysis I Onal, E Aksan, B Velioglu, O Firat, M Ozay, I Oztekin, FTY Vural 2014 22nd International Conference on Pattern Recognition, 3339-3344, 2014 | 3 | 2014 |
| Functional networks of anatomic brain regions B Velioglu, E Aksan, I Onal, O Firat, M Ozay, FTY Vural 2014 IEEE 13th International Conference on Cognitive Informatics and …, 2014 | 3 | 2014 |
| Estimating brain connectivity for pattern analysis I Onal, E Aksan, B Velioglu, O Firat, M Ozay, L Oztekin, FTY Vural 2014 22nd Signal Processing and Communications Applications Conference (SIU …, 2014 | 1 | 2014 |
Otmar HilligesProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
