5 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…
Multiresolution Search of the Rigid Motion Space for Intensity Based Registration
Behrooz Nasihatkon, Fredrik Kahl
We study the relation between the target functions of low-resolution and high-resolution intensity-based registration for the class of rigid transformations. Our results show that…