3 papers
cs.CV2026
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…
cs.CV2025
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…
cs.CV2024
CLFT: Camera-LiDAR Fusion Transformer for Semantic Segmentation in Autonomous Driving
Junyi Gu, Mauro Bellone, Tomáš PivoÅka +1
Critical research about camera-and-LiDAR-based semantic object segmentation for autonomous driving significantly benefited from the recent development of deep learning. Specificall…