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
Interactive multi-modal motion planning with Branch Model Predictive ControlCode1
Interpretable Self-Aware Neural Networks for Robust Trajectory PredictionCode1
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving ScenariosCode1
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement LearningCode1
Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?Code1
Keep your Eyes on the Lane: Real-time Attention-guided Lane DetectionCode1
Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph ConstructionCode1
Lane Graph Estimation for Scene Understanding in Urban DrivingCode1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
A Baseline for the Commands For Autonomous Vehicles ChallengeCode1
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Benchmark Results

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