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Tobias Kirschstein
Tobias Kirschstein
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Title
Cited by
Cited by
Year
Language-agnostic representation learning of source code from structure and context
D Zügner, T Kirschstein, M Catasta, J Leskovec, S Günnemann
arXiv preprint arXiv:2103.11318, 2021
1372021
End-to-end learning for dimensional emotion recognition from physiological signals
G Keren, T Kirschstein, E Marchi, F Ringeval, B Schuller
2017 IEEE International Conference on Multimedia and Expo (ICME), 985-990, 2017
582017
GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians
S Qian, T Kirschstein, L Schoneveld, D Davoli, S Giebenhain, M Nießner
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
412024
NeRSemble: Multi-View Radiance Field Reconstruction of Human Heads
T Kirschstein, S Qian, S Giebenhain, T Walter, M Nießner
ACM Transactions on Graphics (TOG) 42 (4), 161:1-14, 2023
392023
Learning Neural Parametric Head Models
S Giebenhain, T Kirschstein, M Georgopoulos, M Rünz, L Agapito, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
292023
DiffusionAvatars: Deferred Diffusion for High-fidelity 3D Head Avatars
T Kirschstein, S Giebenhain, M Nießner
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
72024
MonoNPHM: Dynamic Head Reconstruction from Monocular Videos
S Giebenhain, T Kirschstein, M Georgopoulos, M Rünz, L Agapito, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
62024
Language-agnostic representation learning of source code from structure and context. arXiv 2021
D Zügner, T Kirschstein, M Catasta, J Leskovec, S Günnemann
arXiv preprint arXiv:2103.11318, 0
5
GGHead: Fast and Generalizable 3D Gaussian Heads
T Kirschstein, S Giebenhain, J Tang, M Georgopoulos, M Nießner
arXiv preprint arXiv:2406.09377, 2024
2024
NPGA: Neural Parametric Gaussian Avatars
S Giebenhain, T Kirschstein, M Rünz, L Agapito, M Nießner
arXiv preprint arXiv:2405.19331, 2024
2024
Supplementary Material: Learning Neural Parametric Head Models
S Giebenhain, T Kirschstein, M Georgopoulos, M Rünz, L Agapito, ...
TUM Data Innovation Lab
J Beck, LM Bernhardt, H Chauhan, T Kirschstein, M Maier-Borst, ...
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