most citedVLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision

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cs.CV2024★ 1 cited

VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision

Yi Xu, Yuxin Hu, Zaiwei Zhang +5

Human drivers rely on commonsense reasoning to navigate diverse and dynamic real-world scenarios. Existing end-to-end (E2E) autonomous driving (AD) models are typically optimized t…

cs.CV2024

Cohere3D: Exploiting Temporal Coherence for Unsupervised Representation Learning of Vision-based Autonomous Driving

Yichen Xie, Hongge Chen, Gregory P. Meyer +6

Due to the lack of depth cues in images, multi-frame inputs are important for the success of vision-based perception, prediction, and planning in autonomous driving. Observations f…