Static adversarial camouflage exploits natural view-angle changes during relative motion to induce consistent feature drift in AV perception, leading to incorrect trajectory predictions and unnecessary braking.
Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Changes in Chain-of-Causation explanations under sensor perturbations correlate with 5.3× higher trajectory deviation in a driving VLA, and enabling such explanations yields 11.8% better accuracy.
citing papers explorer
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Still Camouflage, Moving Illusion: View-Induced Trajectory Manipulation in Autonomous Driving
Static adversarial camouflage exploits natural view-angle changes during relative motion to induce consistent feature drift in AV perception, leading to incorrect trajectory predictions and unnecessary braking.
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Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs
Changes in Chain-of-Causation explanations under sensor perturbations correlate with 5.3× higher trajectory deviation in a driving VLA, and enabling such explanations yields 11.8% better accuracy.