TrustFlip weaponizes consistency-based trust defenses in vehicular collaborative perception by using physical adversarial objects to induce inconsistencies that are misattributed to benign vehicles, leading to their exclusion and reduced system performance.
F-cooper: Feature based cooperative perception for autonomous vehicle edge computing system using 3d point clouds,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
CooperDrive augments autonomous vehicle perception by sharing object-level data from BEV features, enabling earlier conflict anticipation and safer planning with 90 kbps bandwidth and 89 ms latency in real-world NLOS tests.
citing papers explorer
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Adversarial Trust Poisoning in Vehicular Collaborative Perception
TrustFlip weaponizes consistency-based trust defenses in vehicular collaborative perception by using physical adversarial objects to induce inconsistencies that are misattributed to benign vehicles, leading to their exclusion and reduced system performance.
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CooperDrive: Enhancing Driving Decisions Through Cooperative Perception
CooperDrive augments autonomous vehicle perception by sharing object-level data from BEV features, enabling earlier conflict anticipation and safer planning with 90 kbps bandwidth and 89 ms latency in real-world NLOS tests.