arXiv Computer Vision
Calibrating Perception Uncertainty for Autonomous Driving
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Co-GLANCE: Uncertainty-Aware Active Perception for Heterogeneous Robot Teaming
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arXiv Computer Vision
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Semantic Misalignment in Vision-Language Models under Perceptual Degradation
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UP-Fuse: Uncertainty-guided LiDAR-Camera Fusion for 3D Panoptic Segmentation
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What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models
arXiv:2607. 00283v1 Announce Type: cross Abstract: Autonomous vehicles must safely navigate complex environments where planning-critical agents may be hidden from view.
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Closed-Loop Evaluation of Bird's-Eye-View Maps from Cross-View Transformers as Inputs to Behavior-Cloning Policies
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arXiv Machine Learning
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Can Attribution Predict Risk? From Multi-View Attribution to Planning Risk Signals in End-to-End Autonomous Driving
arXiv:2605. 06264v2 Announce Type: replace Abstract: End-to-end autonomous driving models generate future trajectories from multi-view inputs, improving system integration but introducing opaque decisions and hard-to-localize risks.