When the Score Becomes the Target: Rethinking Metric Validity in Autonomous Driving
Do benchmark score gains still reflect real driving improvements once the score becomes the optimization target? Controlled experiments say: not necessarily.
#autonomous driving
Content tagged with "autonomous driving"
LANTERN: A Closed-Loop Benchmark for VLM-Based Cooperative Driving with Temporally Grounded Warnings
A closed-loop benchmark evaluating how vision-language models respond to temporally grounded safety warnings in cooperative driving.
Mind the Hitch: Dynamic Calibration and Articulated Perception for Autonomous Trucks
dCAP: a vision-based framework that continuously estimates the 6-DoF relative pose between tractor and trailer cameras, plus the STT4AT benchmark for articulated trucks.
M³CAD: Towards Generic Cooperative Autonomous Driving Benchmark
A generic benchmark for cooperative autonomous driving supporting multi-vehicle, multi-modal, and multi-task evaluation.
From Features to Reference Points: Lightweight and Adaptive Fusion for Cooperative Autonomous Driving
A lightweight and adaptive reference-point-based fusion approach for cooperative autonomous driving.
Investigating Crowdsourced Neural Radiance Maps for Autonomous Vehicles
Investigating the use of crowdsourced neural radiance fields (NeRF) as maps for autonomous vehicles.
dCAP
Dynamic Calibration and Articulated Perception for autonomous trucks (CVPR 2026).
M³CAD
Towards generic cooperative autonomous driving benchmark (ICRA 2026).