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Lucas Stoffl
Lucas Stoffl
EPFL
在 epfl.ch 的电子邮件经过验证
标题
引用次数
引用次数
年份
End-to-end trainable multi-instance pose estimation with transformers
L Stoffl, M Vidal, A Mathis
arXiv preprint arXiv:2103.12115, 2021
472021
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
242023
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
242017
Could ChatGPT get an engineering degree? Evaluating higher education vulnerability to AI assistants
B Borges, N Foroutan, D Bayazit, A Sotnikova, S Montariol, T Nazaretzky, ...
Proceedings of the National Academy of Sciences 121 (49), e2414955121, 2024
42024
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
22022
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
22020
Elucidating the hierarchical nature of behavior with masked autoencoders
L Stoffl, A Bonnetto, S d’Ascoli, A Mathis
European Conference on Computer Vision, 106-125, 2025
12025
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