We are very happy that our paper “CLEO: Continual Learning of Evolving Ontologies” has been accepted to the European Conference on Computer Vision (ECCV). A preprint of our work can be found here. The paper is a joint work with ZF Friedrichshafen AG and describes some results of our collaboration.
We are proud to announce that our paper “RMS-FlowNet++: Efficient and Robust Multi-scale Scene Flow Estimation for Large-Scale Point Clouds” by Ramy Battrawy, René Schuster, and Didier Stricker has been published in the International Journal of Computer Vision (IJCV). The online version of the paper can be found here a preprint is available here. The paper extends our previous work on efficient scene flow estimation in dense point clouds that has been published at ICRA 2022.