| End-to-end trainable multi-instance pose estimation with transformers L Stoffl, M Vidal, A Mathis arXiv preprint arXiv:2103.12115, 2021 | 40 | 2021 |
| On the use of deep recurrent neural networks for detecting audio spoofing attacks S Scardapane, L Stoffl, F Röhrbein, A Uncini 2017 International Joint Conference on Neural Networks (IJCNN), 3483-3490, 2017 | 21 | 2017 |
| Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity M Zhou*, L Stoffl*, M Mathis, A Mathis IEEE/CVF International Conference on Computer Vision (ICCV), 14689-14699 …, 2023 | 6 | 2023 |
| A neural network family for systematic analysis of RF size and computational-path-length distribution as determinants of neural predictivity and behavioral performance B Peters, L Stoffl, N Kriegeskorte Journal of Vision 22 (14), 4287-4287, 2022 | 1 | 2022 |
| How are response properties in the middle temporal area related to inference on visual motion patterns? O Rezai, L Stoffl, B Tripp Neural Networks 121, 122-131, 2020 | 1 | 2020 |
