4 papers
Unsupervised Monocular Road Segmentation for Autonomous Driving via Scene Geometry
Sara Hatami Rostami, Behrooz Nasihatkon
This paper presents a fully unsupervised approach for binary road segmentation (road vs. non-road), eliminating the reliance on costly manually labeled datasets. The method leverag…
ToosiCubix: Monocular 3D Cuboid Labeling via Vehicle Part Annotations
Behrooz Nasihatkon, Hossein Resani, Amirreza Mehrzadian
Many existing methods for 3D cuboid annotation of vehicles rely on expensive and carefully calibrated camera-LiDAR or stereo setups, limiting their accessibility for large-scale da…
MIRACLE3D: Memory-efficient Integrated Robust Approach for Continual Learning on Point Clouds via Shape Model Construction
Hossein Resani, Behrooz Nasihatkon
In this paper, we introduce a novel framework for memory-efficient and privacy-preserving continual learning in 3D object classification. Unlike conventional memory-based approache…
Continual Learning in 3D Point Clouds: Employing Spectral Techniques for Exemplar Selection
Hossein Resani, Behrooz Nasihatkon, Mohammadreza Alimoradi Jazi
We introduce a novel framework for Continual Learning in 3D object classification. Our approach, CL3D, is based on the selection of prototypes from each class using spectral cluste…