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 841–850 of 2605 papers

TitleStatusHype
Efficient Sampling-Based Maximum Entropy Inverse Reinforcement Learning with Application to Autonomous Driving—0
Efficient statistical validation with edge cases to evaluate Highly Automated Vehicles—0
A machine learning environment for evaluating autonomous driving software—0
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting—0
Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout—0
EGA-Depth: Efficient Guided Attention for Self-Supervised Multi-Camera Depth Estimation—0
EgoVM: Achieving Precise Ego-Localization using Lightweight Vectorized Maps—0
Electric Autonomous Mobility-on-Demand: Jointly Optimal Vehicle Design and Fleet Operation—0
Electric Vehicle E-hailing Fleet Dispatching and Charge Scheduling—0
DeepLaser: Practical Fault Attack on Deep Neural Networks—0
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Benchmark Results

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