| 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 | 41 | 2024 |
| 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), 1-14, 2023 | 39 | 2023 |
| 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 | 29 | 2023 |
| Radar Ghost Target Detection via Multimodal Transformers LC Wang, S Giebenhain, C Anklam, B Goldluecke IEEE Robotics and Automation Letters 6 (4), 7758-7765, 2021 | 19 | 2021 |
| Air-nets: An attention-based framework for locally conditioned implicit representations S Giebenhain, B Goldlücke 2021 International Conference on 3D Vision (3DV), 1054-1064, 2021 | 14 | 2021 |
| 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 | 7 | 2024 |
| 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 | 6 | 2024 |
| Neural Puppeteer: Keypoint-Based Neural Rendering of Dynamic Shapes S Giebenhain, U Waldmann, O Johannsen, B Goldluecke Proceedings of the Asian Conference on Computer Vision, 2830-2847, 2022 | 4 | 2022 |
| NPGA: Neural Parametric Gaussian Avatars S Giebenhain, T Kirschstein, M Rünz, L Agapito, M Nießner arXiv preprint arXiv:2405.19331, 2024 | | 2024 |
| HeadCraft: Modeling High-Detail Shape Variations for Animated 3DMMs A Sevastopolsky, PW Grassal, S Giebenhain, SR Athar, L Verdoliva, ... arXiv preprint arXiv:2312.14140, 2023 | | 2023 |
| Multiple Object Tracking Based on Paint Patterns S Giebenhain Universität Konstanz, 2020 | | 2020 |
| Supplementary Material: Learning Neural Parametric Head Models S Giebenhain, T Kirschstein, M Georgopoulos, M Rünz, L Agapito, ... | | |
