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DriveZero is an end-to-end autonomous driving system that combines a vision foundation model for perception with reinforcement learning for action, achieving driving behaviors beyond human demonstrations and state-of-the-art performance on benchmarks like nuPlan and NAVSIM.
V-RAE proposes a video representation autoencoder that builds semantically organized latents from frozen vision representations to enhance video generation quality, convergence speed, and predictive modeling.
The paper proposes Geo-Anchored Cloud Removal (GACR), a framework that uses Observation-Anchored Residual Flow and Geo-Contextual Prior Alignment to remove clouds from optical remote sensing images while preserving semantic structures for downstream tasks.