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 311–320 of 2605 papers

TitleStatusHype
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?Code1
Categorical Depth Distribution Network for Monocular 3D Object DetectionCode1
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous VehiclesCode1
Fooling LiDAR Perception via Adversarial Trajectory PerturbationCode1
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy FeaturesCode1
Fourier Prompt Tuning for Modality-Incomplete Scene SegmentationCode1
Bootstrapping Autonomous Driving Radars with Self-Supervised LearningCode1
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object DetectionCode1
Monitoring and Adapting the Physical State of a Camera for Autonomous VehiclesCode1
CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal RelationshipsCode1
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Benchmark Results

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