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 1001–1010 of 2605 papers

TitleStatusHype
Autonomous Vehicles as a Sensor: Simulating Data Collection Process—0
Evaluating Pedestrian Trajectory Prediction Methods with Respect to Autonomous Driving—0
Leveraging the Edge and Cloud for V2X-Based Real-Time Object Detection in Autonomous Driving—0
An Empirical Analysis of Range for 3D Object Detection—0
An Approximate Dynamic Programming Approach to Vehicle Platooning Coordination in Networks—0
Vehicle Motion Forecasting using Prior Information and Semantic-assisted Occupancy Grid Maps—0
Analytical Safety Bounds for Trajectory Following Controllers in Autonomous Vehicles—0
Communication-Efficient Decentralized Multi-Agent Reinforcement Learning for Cooperative Adaptive Cruise Control—0
Robust Self-Supervised Extrinsic Self-Calibration—0
A Counterfactual Safety Margin Perspective on the Scoring of Autonomous Vehicles' RiskinessCode1
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Benchmark Results

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