3 accepted papers
In visual simultaneous localization and mapping (SLAM), the quality of the visual vocabulary is fundamental to the system's ability to represent environments and recognize locations. While ORB-SLAM is a widely used framework, its binary vocabulary, trained through the k-majority-based bag-of-words (…
We propose a framework for privacy-preserving argumentative explanations using homomorphic encryption. This method applies the Cheon-Kim-Kim-Song scheme, along with a soft k-means adapted for encrypted computation, to generate explanations without exposing sensitive data. By leveraging GPU accelerat
Moving object segmentation (MOS) is foundational for autonomous vehicle safety. However, the increasing diversity of LiDAR sensors creates a significant domain shift problem, causing models trained on one sensor to perform poorly when deployed on another. A naive approach of training on combined dat…