6 papers
To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software
Loïc Stratil, Felix Fent, Esteban Rivera +1
Autonomous vehicle perception typically relies on modular pipelines that decompose the task into detection, tracking, and prediction. While interpretable, these pipelines suffer fr…
VESPA: Towards un(Human)supervised Open-World Pointcloud Labeling for Autonomous Driving
Levente Tempfli, Esteban Rivera, Markus Lienkamp
Data collection for autonomous driving is rapidly accelerating, but manual annotation, especially for 3D labels, remains a major bottleneck due to its high cost and labor intensity…
HeAL3D: Heuristical-enhanced Active Learning for 3D Object Detection
Esteban Rivera, Surya Prabhakaran, Markus Lienkamp
Active Learning has proved to be a relevant approach to perform sample selection for training models for Autonomous Driving. Particularly, previous works on active learning for 3D…
Inconsistency-based Active Learning for LiDAR Object Detection
Esteban Rivera, Loic Stratil, Markus Lienkamp
Deep learning models for object detection in autonomous driving have recently achieved impressive performance gains and are already being deployed in vehicles worldwide. However, c…
V3LMA: Visual 3D-enhanced Language Model for Autonomous Driving
Jannik Lübberstedt, Esteban Rivera, Nico Uhlemann +1
Large Vision Language Models (LVLMs) have shown strong capabilities in understanding and analyzing visual scenes across various domains. However, in the context of autonomous drivi…
Scenario Understanding of Traffic Scenes Through Large Visual Language Models
Esteban Rivera, Jannik Lübberstedt, Nico Uhlemann +1
Deep learning models for autonomous driving, encompassing perception, planning, and control, depend on vast datasets to achieve their high performance. However, their generalizatio…