4 papers
CLFTv2: Efficient Camera-LiDAR Fusion for Semantic Segmentation via Hierarchical Feature Pyramids
Toomas Tahves, Mauro Bellone, Raivo Sell
Semantic segmentation for autonomous driving requires reliable detection of vulnerable road users (VRUs) despite heavy class imbalance. We introduce CLFTv2, a hierarchical camera-L…
SAM-Enhanced Segmentation on Road Datasets: Balancing Critical Classes in Autonomous Driving
Toomas Tahves, Mauro Bellone, Junyi Gu +1
Dense semantic segmentation is essential for autonomous driving, yet many multi-modal datasets lack pixel-level annotations. The Zenseact Open Dataset (ZOD) provides rich multi-sen…
A Novel Vision Transformer for Camera-LiDAR Fusion based Traffic Object Segmentation
Toomas Tahves, Junyi Gu, Mauro Bellone +1
This paper presents Camera-LiDAR Fusion Transformer (CLFT) models for traffic object segmentation, which leverage the fusion of camera and LiDAR data using vision transformers. Bui…
CLFT: Camera-LiDAR Fusion Transformer for Semantic Segmentation in Autonomous Driving
Junyi Gu, Mauro Bellone, Tomáš Pivoňka +1
Critical research about camera-and-LiDAR-based semantic object segmentation for autonomous driving significantly benefited from the recent development of deep learning. Specificall…