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cs.CV2024
ACT-Bench: Towards Action Controllable World Models for Autonomous Driving
Hidehisa Arai, Keishi Ishihara, Tsubasa Takahashi +1
World models have emerged as promising neural simulators for autonomous driving, with the potential to supplement scarce real-world data and enable closed-loop evaluations. However…
cs.CV2024★ 1 cited
CoVLA: Comprehensive Vision-Language-Action Dataset for Autonomous Driving
Hidehisa Arai, Keita Miwa, Kento Sasaki +4
Autonomous driving, particularly navigating complex and unanticipated scenarios, demands sophisticated reasoning and planning capabilities. While Multi-modal Large Language Models…