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 2131–2140 of 2605 papers

TitleStatusHype
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review—0
Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction—0
Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental StudyCode1
Real-Time Segmentation Networks should be Latency Aware—0
TensorFI: A Flexible Fault Injection Framework for TensorFlow ApplicationsCode1
Context-Aware Multi-Task Learning for Traffic Scene Recognition in Autonomous Vehicles—0
Exploration of Reinforcement Learning for Event Camera using Car-like Robots—0
Statistical Verification of Autonomous Systems using Surrogate Models and Conformal Inference—0
Covariance-Robust Dynamic Watermarking—0
EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning—0
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Benchmark Results

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