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 211–220 of 2605 papers

TitleStatusHype
BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous DrivingCode1
Fooling LiDAR Perception via Adversarial Trajectory PerturbationCode1
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving ScenariosCode1
DR-TANet: Dynamic Receptive Temporal Attention Network for Street Scene Change DetectionCode1
Ford Multi-AV Seasonal DatasetCode1
BAAM: Monocular 3D Pose and Shape Reconstruction With Bi-Contextual Attention Module and Attention-Guided ModelingCode1
A Baseline for the Commands For Autonomous Vehicles ChallengeCode1
LiDAR-based 4D Occupancy Completion and ForecastingCode1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal RelationshipsCode1
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Benchmark Results

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