Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavior constrained by the quality and behavioral coverage of the recorded trajectories. This report presents DriveZero, an end-to-end system that learns driving behavior beyond human demonstrations. It decomposes d...
Hao He, Cheng-Cheng Hu, Zi-Run Su et al.· 0 citations
Novel view synthesis from sparse inputs requires both geometric grounding from the observed views and generative priors of unobserved regions, motivating recent hybrid methods that combine reconstruction and generation. However, existing methods bridge the two with rendered images or explicit 3D representations such as...
Xiaolei Lang, Ze Kang, Ze-Hao Huang et al.· 0 citations
Camera-based autonomous driving perception requires a shared representation that preserves metric 3D structure across synchronized multi-camera streams. However, existing image-based frameworks often rely on backbones pretrained for semantic recognition, and introduce 3D geometry through downstream task-specific module...
Longfei Xu, Xiao-Hui Wang, Ze-Hao Huang et al.· 2 citations
The ViSTR-Bench is introduced, a novel evaluation suite designed to systematically assess whether MLLMs can perform qualitative reasoning from continuous visual cues in dynamic scenes and establishes a comprehensive four-dimensional evaluations covering Motion Perception, Spatial Relations, Outcome Prediction, and Phys...
Han Li, Si Liu, Zehao Huang et al.· arXiv.org· 1 citation
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