Prof. Dr. Bernhard Egger

2025

• Buschmann, B., Dogaru, A., Eisemann, E., Weinmann, M., & Egger, B. (2025). RANRAC: Robust Neural Scene Representations via Random Ray Consensus. In Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 126-143). Milan, IT: Springer Science and Business Media Deutschland GmbH.
• Dogaru, A., Özer, M., & Egger, B. (2025). Generalizable 3D Scene Reconstruction via Divide and Conquer from a Single View. In Proceedings of the International Conference on 3D Vision 2025. Singapore, SG.
• Gardner, J.A., Kashin, E., Egger, B., & Smith, W.A. (2025). The Sky’s the Limit: Relightable Outdoor Scenes via a Sky-Pixel Constrained Illumination Prior and Outside-In Visibility. In Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 126-143). Milan, ITA: Springer Science and Business Media Deutschland GmbH.
• Namayega, C., Borotikar, B., Menten, M., Gibbon, V., Thusini, X., Egger, B.,... Mutsvangwa, T.E. (2025). Capturing Complexity of the Foot Arch Bones: Evaluation of a Statistical Modelling Framework for Learning Shape, Pose and Intensity Features in a Continuous Domain. In Udunna Anazodo, Naren Akash, Moritz Fuchs, Celia Cintas, Alessandro Crimi, Tinahse Mutsvangwa, Farouk Dako, Willam Ogallo (Eds.), Medical Information Computing. First MICCAI Meets Africa Workshop, MImA 2024, and First MICCAI Student Board Workshop on Empowering Medical Information Computing and Research through Early-Career Expertise, EMERGE 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Revised Selected Papers (pp. 153-163). Marrakesh, MA: Cham: Springer.
• Weiherer, M., & Egger, B. (2025). MATÉRN KERNELS FOR TUNABLE IMPLICIT SURFACE RECONSTRUCTION. In 13th International Conference on Learning Representations, ICLR 2025 (pp. 66102-66123). Singapore, SGP: International Conference on Learning Representations, ICLR.
• Weiherer, M., von Riedheim, A., Brébant, V., Egger, B., & Palm, C. (2025). iRBSM: A Deep Implicit 3D Breast Shape Model. In Christoph Palm, Katharina Breininger, Thomas Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Thomas M. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2025. Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025 (pp. 38-43). Regensburg, DE: Cham: Springer.

2024

• Dey, R., Egger, B., Boddeti, V.N., Wang, Y., & Marks, T.K. (2024). CoLa-SDF: Controllable Latent StyleSDF for Disentangled 3D Face Generation. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp. 2852-2861). Seattle, WA, USA: IEEE Computer Society.
• Drobnitzky, M., Friederich, J., Egger, B., & Zschech, P. (2024). Survey and systematization of 3D object detection models and methods. Visual Computer, 40(3), 1867-1913. https://doi.org/10.1007/s00371-023-02891-1
• Keinert, E.M., Schindler-Gmelch, L., Rupp, L., Sadeghi, M., Capito, K., Hager, M.,... Berking, M. (2024). Facing depression: evaluating the efficacy of the EmpkinS-EKSpression reappraisal training augmented with facial expressions – protocol of a randomized controlled trial. BMC Psychiatry, 24. https://doi.org/10.1186/s12888-024-06361-3
• Li, S., Schieber, H., Corell, N., Egger, B., Kreimeier, J., & Roth, D. (2024). GBOT: Graph-Based 3D Object Tracking for Augmented Reality-Assisted Assembly Guidance. In Proceedings - 2024 IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2024 (pp. 513-523). Orlando, FL, US: Institute of Electrical and Electronics Engineers Inc..
• Ni, H., Egger, B., Lohit, S., Cherian, A., Wang, Y., Koike-Akino, T.,... Marks, T.K. (2024). TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 9015-9025). Seattle, WA, US: IEEE Computer Society.
• Nishimura, T., Dogaru, A., & Egger, B. (2024). ArCSEM: Artistic Colorization of SEM Images via Gaussian Splatting. In Proceedings of the AI for Visual Arts Workshop and Challenges (AI4VA) in conjunction with European Conference on Computer Vision (ECCV) 2024, Milano, Italy. Mailand, IT.
• Penk, D., Horn, M., Strohmeyer, C., Egger, B., Stamminger, M., & Bauer, F. (2024). AbSynth: Using Abstract Image Synthesis for Synthetic Training. In Petia Radeva, Antonino Furnari, Kadi Bouatouch, A. Augusto Sousa (Eds.), Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 718-729). Rome, ITA: Science and Technology Publications, Lda.
• Riedmann, F., Egger, B., & Rohe, T. (2024). Revealing an Unattractivity Bias in Mental Reconstruction of Occluded Faces using Generative Image Models. In Proceedings of the Cognitive Computational Neuroscience. Boston, US.
• Sadeghi, M., Egger, B., Agahi, R., Richer, R., Capito, K., Rupp, L.,... Eskofier, B. (2024). Exploring the Capabilities of a Language Model-Only Approach for Depression Detection in Text Data. In Proceedings of the Deutscher Psychotherapiekongress (DPK). Berlin.
• Sadeghi, M., Richer, R., Egger, B., Schindler-Gmelch, L., Rupp, L., Rahimi, F.,... Eskofier, B. (2024). Harnessing multimodal approaches for depression detection using large language models and facial expressions. npj Mental Health Research, 3(1), 66. https://doi.org/10.1038/s44184-024-00112-8
• Schieber, H., Deuser, F., Egger, B., Oswald, N., & Roth, D. (2024). NeRFtrinsic Four: An end-to-end trainable NeRF jointly optimizing diverse intrinsic and extrinsic camera parameters. Computer Vision and Image Understanding, 249. https://doi.org/10.1016/j.cviu.2024.104206
• Shetty, K., Birkhold, A., Egger, B., Jaganathan, S., Strobel, N., Kowarschik, M., & Maier, A. (2024). HOOREX: Higher Order Optimizers for 3D Recovery from X-Ray Images. In Andreas K. Maier, Julia A. Schnabel, Pallavi Tiwari, Oliver Stegle (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 115-124). Honolulu, HI, USA: Springer Science and Business Media Deutschland GmbH.
• Zieger, D., Güthlein, F., Henningson, J.-O., Jakob, V., Gaßner, H., Shanbhag, J.,... Stamminger, M. (2024). 3D Body Twin: Improving Human Gait Visualizations Using Personalized Avatars. In ShapeMI 2024 (pp. 70-83). Marrakesh, MA.

2023

• Atuhaire, F., Egger, B., & Mutsvangwa, T. (2023). Evaluating 3D human face reconstruction from a frontal 2D image, focusing on facial regions associated with foetal alcohol syndrome. South African Journal of Science, 119(3-4). https://dx.doi.org/10.17159/sajs.2023/12064
• Cappell, B., Stoll, A., Umah, W.C., & Egger, B. (2023). ReWaRD: Retinal Waves for Pre-Training Artificial Neural Networks Mimicking Real Prenatal Development. In Marco Fumero, Emanuele Rodola, Clementine C. J. Domine, Francesco Locatello, Gintare Karolina Dziugaite, Mathilde Caron (Eds.), Proceedings of Machine Learning Research (pp. 1-10). New Orleans, LA, USA: ML Research Press.
• Choithwani, M., Almeida, S., & Egger, B. (2023). PoseBias: On Dataset Bias and Task Difficulty - Is there an Optimal Camera Position for Facial Image Analysis? In 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) (pp. 3088-3096). Paris, FR: Institute of Electrical and Electronics Engineers Inc..
• Li, C., Morel-Forster, A., Vetter, T., Egger, B., & Kortylewski, A. (2023). Robust Model-based Face Reconstruction through Weakly-Supervised Outlier Segmentation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 372-381). Vancouver, BC, CA: IEEE Computer Society.
• Sadeghi, M., Egger, B., Agahi, R., Richer, R., Capito, K., Rupp, L.,... Eskofier, B. (2023). Exploring the Capabilities of a Language Model-Only Approach for Depression Detection in Text Data. In IEEE EMBS International Conference on Biomedical and Health Informatics (BHI) (pp. 5). Pittsburgh, PA, USA, US: IEEE.
• Shetty, K., Birkhold, A., Jaganathan, S., Strobel, N., Egger, B., Kowarschik, M., & Maier, A. (2023). BOSS: Bones, organs and skin shape model. Computers in Biology and Medicine, 165. https://doi.org/10.1016/j.compbiomed.2023.107383
• Shetty, K., Birkhold, A., Jaganathan, S., Strobel, N., Kowarschik, M., Maier, A., & Egger, B. (2023). PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 574-584). Vancouver, BC, CA: IEEE Computer Society.
• Sutherland, S., Egger, B., & Tenenbaum, J. (2023). Building 3D Generative Models from Minimal Data. International Journal of Computer Vision. https://dx.doi.org/10.1007/s11263-023-01870-2
• Tretschk, E., Kairanda, N., Mallikarjun, B.R., Dabral, R., Kortylewski, A., Egger, B.,... Golyanik, V. (2023). State of the Art in Dense Monocular Non-Rigid 3D Reconstruction. Computer Graphics Forum, 42(2), 485-520. https://doi.org/10.1111/cgf.14774
• Wirth, V., Liphardt, A.-M., Coppers, B., Bräunig, J., Heinrich, S., Leyendecker, S.,... Stamminger, M. (2023). Markerless RGB-D Hand Pose Estimation for Activity Monitoring of Musculoskeletal Diseases. Poster presentation at IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI’23), Pittsburgh, USA.
• Wirth, V., Liphardt, A.-M., Coppers, B., Bräunig, J., Heinrich, S., Leyendecker, S.,... Stamminger, M. (2023). ShaRPy: Shape Reconstruction and Hand Pose Estimation from RGB-D with Uncertainty. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops (pp. 2625-2633). Paris, FR.

2022

• Gardner, J.A., Egger, B., & Smith, W.A. (2022). Rotation-Equivariant Conditional Spherical Neural Fields for Learning a Natural Illumination Prior. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh (Eds.), Advances in Neural Information Processing Systems. New Orleans, LA, USA: Neural information processing systems foundation.
• Marcus, R., Knoop, N., Egger, B., & Stamminger, M. (2022). A Lightweight Machine Learning Pipeline for LiDAR-simulation. In DELTA: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON DEEP LEARNING THEORY AND APPLICATIONS (pp. 176-183). Lisbon, PT: SETUBAL: SCITEPRESS.
• Medin, S.C., Egger, B., Cherian, A., Wang, Y., Tenenbaum, J.B., Liu, X., & Marks, T.K. (2022). MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation. In THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / THE TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE (pp. 1962-1971). PALO ALTO: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
• Weiherer, M., Eigenberger, A., Egger, B., Brébant, V., Prantl, L., & Palm, C. (2022). Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans. Visual Computer. https://doi.org/10.1007/s00371-022-02431-3

2021

• Chang, L., Egger, B., Vetter, T., & Tsao, D.Y. (2021). Explaining face representation in the primate brain using different computational models. Current Biology, 31(13), 2785-2795.e4. https://doi.org/10.1016/j.cub.2021.04.014
• Egger, B., Sutherland, S., Medin, S.C., & Tenenbaum, J. (2021). Identity-Expression Ambiguity in 3D Morphable Face Models. In 2021 16TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2021). NEW YORK: IEEE.
• Shetty, K., Birkhold, A., Strobel, N., Egger, B., Jaganathan, S., Kowarschik, M., & Maier, A. (2021). Deep Learning Compatible Differentiable X-ray Projections for Inverse Rendering. In Christoph Palm, Heinz Handels, Klaus Maier-Hein, Thomas M. Deserno, Andreas Maier, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 290-295). Regensburg, DE: Springer Science and Business Media Deutschland GmbH.

2020

• Egger, B., Smith, W.A.P., Tewari, A., Wuhrer, S., Zollhoefer, M., Beeler, T.,... Vetter, T. (2020). 3D Morphable Face Modelsa-Past, Present, and Future. Acm Transactions on Graphics, 39(5). https://doi.org/10.1145/3395208
• Smith, W.A.P., Seck, A., Dee, H., Tiddeman, B., Tenenbaum, J.B., & Egger, B. (2020). A morphable face Albedo model. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 5010-5019). Virtual, Online, USA: IEEE Computer Society.