SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

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Showing 421–430 of 2605 papers

TitleStatusHype
Securing Traffic Sign Recognition Systems in Autonomous Vehicles—0
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle PerceptionCode0
DriveAction: A Benchmark for Exploring Human-like Driving Decisions in VLA Models—0
Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light DetectorsCode0
Towards provable probabilistic safety for scalable embodied AI systems—0
How stealthy is stealthy? Studying the Efficacy of Black-Box Adversarial Attacks in the Real World—0
High-gain MIMO Beamforming Antenna System for DSRC and mmwave 5G Integration in Autonomous Vehicles—0
Integrated Sensing, Computing and Semantic Communication for Vehicular Networks—0
S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Modelwith Spatio-Temporal Visual Representation—0
Distributed Federated Learning for Vehicular Network Security: Anomaly Detection Benefits and Multi-Domain Attack Threats—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified