Olaf Hellwich

TU Berlin, Computer Vision
phone: +49 30 314 22796

Olaf Hellwich contributes to the autonomous acquisition of prior knowledge from visual experience and the application of the priors learned from that experience. He posseses expertise in feature extraction, learning of object models from features, 3D object reconstruction, and most recently deep learning.

At SCIoI, Olaf Hellwich is working on Project 01, Project 25, Project 29, Project 40, Project 57.

 

 

 

SCIoI Publications

Roth, N., Rolfs, M., Hellwich, O., & Obermayer, K. (2023). Diminished state space theory of human aging. PsyArXiv. https://doi.org/10.31219/osf.io/x7wpj
Roth, N., Rolfs, M., Hellwich, O., & Obermayer, K. (2023). Objects guide human gaze behavior in dynamic real-world scenes. bioRxiv. https://doi.org/10.1101/2023.03.14.532608
Maier, M., Blume, F., Bideau, P., Hellwich, O., & Abdel Rahman, R. (2022). Knowledge-Augmented Face Perception: Prospects for the Bayesian Brain-Framework to Align AI and Human Vision. Consciousness and Cognition, 101. https://doi.org/10.1016/j.concog.2022.103301
Halawa, M., Hellwich, O., & Bideau, P. (2022). Action based Contrastive Learning for Trajectory Prediction. European Conference on Computer Vision (ECCV), 143–159. https://doi.org/10.1007/978-3-031-19842-7_9
Roth, N., Bideau, P., Hellwich, O., Rolfs, M., & Obermayer, K. (2021). Modeling the influence of objects on saccadic decisions in dynamic real-world scenes. PERCEPTION / 43rd European Conference on Visual Perception (ECVP) 2021. https://journals.sagepub.com/doi/full/10.1177/03010066211059887
Roth, N., Bideau, P., Hellwich, O., Rolfs, M., & Obermayer, K. (2021). A modular framework for object-based saccadic decisions in dynamic scenes. CVPR EPIC Workshop / arXiv:2106.06073. https://doi.org/10.48550/arXiv.2106.06073
Halawa, M., Wollhaf, M., Vellasques, E., Sanchez Sanz, U., Urko Sanz, & Hellwich, O. (2020). Learning Disentangled Expression Representations from Facial Images. arxiv and WiCV at ECCV2020. https://doi.org/10.48550/arXiv.2008.07001
Andresen, N., Wöllhaf, M., Hohlbaum, K., Lewejohann, L., Hellwich, O., Thöne-Reineke, C., & Belik, V. (2020). Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expression analysis. PLOS ONE, 15(4), e0228059. https://doi.org/10.1371/journal.pone.0228059