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 1121–1130 of 2605 papers

TitleStatusHype
Local and Global Contextual Features Fusion for Pedestrian Intention Prediction—0
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object DetectionCode1
Decision Making for Autonomous Vehicles—0
Gradient-based Maximally Interfered Retrieval for Domain Incremental 3D Object DetectionCode0
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy FeaturesCode1
Lane Change Intention Recognition and Vehicle Status Prediction for Autonomous Vehicles—0
SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge—0
End-to-End Lidar-Camera Self-Calibration for Autonomous Vehicles—0
A hierarchical adaptive nonlinear model predictive control approach for maximizing tire force usage in autonomous vehicles—0
Interruption-Aware Cooperative Perception for V2X Communication-Aided Autonomous Driving—0
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Benchmark Results

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