Downloads

Hier finden Sie zukünftig die Projekt-Deliverables zum Download.

Deliverables

Veröffentlichungen

publications

Oberdiek, Philipp and Rottmann, Matthias and Fink, Gernot A.: Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, pp. 328-329
Schwarz, Katja and Liao, Yiyi and Niemeyer, Michael and Geiger, Andreas: GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis. In: Part of Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020). Presentation available here.
Schutera, Mark and Hussein, Mostafa and Abhau, Jochen and Mikut, Ralf and Reischl, Markus: Night-to-Day: Online Image-to-Image Translation for Object Detection Within Autonomous Driving by Night. In: IEEE Transactions on Intelligent Vehicles
Schutera, Mark and Hafner, Frank M. and Abhau, Jochen and Hagenmeyer, Veit and Mikut, Ralf and Reischl, Markus: Cuepervision: self-supervised learning for continuous domain adaptation without catastrophic forgetting. In: Vision and Image Computing as part of the special issue: Advances in Domain Adaptation for Computer Vision.
Monka, Sebastian and Halilaj, Lavdim and Rettinger, Achim: A Survey on Visual Transfer Learning using Knowledge Graphs. In: Semantic Web Journal (SWJ, IOS Press).
Monka, Sebastian and Halilaj, Lavdim and Schmid, Stefan and Rettinger, Achim: ConTraKG: Contrastive-based Transfer Learning for Visual Object Recognition using Knowledge Graphs. In: arXiv.
Sauer, Axel and Geiger, Andreas: Counterfactual Generative Networks. In: ICLR 2021 (International Conference on Learning Representations).

Hier werden die öffentlichen Präsentationen des Projektes gelistet.

Präsentationen

presentations

November 9, 2020

Präsentation von KI Delta Learning durch den Projektkoordinator Mohsen Sefati auf der gemeinsamen Veranstaltung des Bundesministeriums für Wirtschaft und Energie und des VDA

Automobilindustrie-digital_04_Praesentation_KI-DL_M_Sefati.pdf(pdf:3 MB)