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 1261–1270 of 2605 papers

TitleStatusHype
Fusion-GRU: A Deep Learning Model for Future Bounding Box Prediction of Traffic Agents in Risky Driving Videos—0
Defensive Perception: Estimation and Monitoring of Neural Network Performance under Deployment—0
Hardware Accelerators in Autonomous Driving—0
FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks—0
Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving—0
Leveraging the Edge and Cloud for V2X-Based Real-Time Object Detection in Autonomous Driving—0
Evaluating Pedestrian Trajectory Prediction Methods with Respect to Autonomous Driving—0
Autonomous Vehicles as a Sensor: Simulating Data Collection Process—0
Vehicle Motion Forecasting using Prior Information and Semantic-assisted Occupancy Grid Maps—0
An Empirical Analysis of Range for 3D Object Detection—0
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Benchmark Results

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