7 papers
SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning
Sviatoslav Voloshyn, Bruno K. W. Martens, Wangxin Liu +2
This paper presents SD-RouteFusion, a deployable end-to-end ego-trajectory prediction method that fuses a front-facing camera, vehicle kinematics, and a navigation route derived fr…
QueryOcc: Query-based Self-Supervision for 3D Semantic Occupancy
Adam Lilja, Ji Lan, Junsheng Fu +1
Learning 3D scene geometry and semantics from images is a core challenge in computer vision and a key capability for autonomous driving. Since large-scale 3D annotation is prohibit…
Beyond Chamfer Distance: Granular Order-aware Evaluation Metric For Online Mapping
Chouaib Bencheikh Lehocine, Adam Lilja, Junsheng Fu +1
Online map estimation is a crucial component of autonomous driving systems that reduces the reliance on costly high-definition maps. State-of-the-art (SOTA) methods commonly predic…
BF-Map: Crowd-sourced Mapping with Bayesian B-spline Fusion
Yiping Xie, Yuxuan Xia, Erik Stenborg +5
Crowd-sourced mapping offers a scalable alternative to creating maps using traditional survey vehicles. Yet, existing methods either rely on prior high-definition (HD) maps or negl…
Driving with Context: Online Map Matching for Complex Roads Using Lane Markings and Scenario Recognition
Xin Bi, Zhichao Li, Yuxuan Xia +4
Accurate online map matching is fundamental to vehicle navigation and the activation of intelligent driving functions. Current online map matching methods are prone to errors in co…
Exploring Semi-Supervised Learning for Online Mapping
Adam Lilja, Erik Wallin, Junsheng Fu +1
The ability to generate online maps using only onboard sensory information is crucial for enabling autonomous driving beyond well-mapped areas. Training models for this task -- pre…