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 1651–1660 of 2605 papers

TitleStatusHype
A Quality Index Metric and Method for Online Self-Assessment of Autonomous Vehicles Sensory Perception—0
Bilateral Deep Reinforcement Learning Approach for Better-than-human Car Following Model—0
Physical Backdoor Attacks to Lane Detection Systems in Autonomous Driving—0
Explaining RADAR features for detecting spoofing attacks in Connected Autonomous Vehicles—0
Deep Camera Pose Regression Using Pseudo-LiDAR—0
RONELDv2: A faster, improved lane tracking method—0
"Is not the truth the truth?": Analyzing the Impact of User Validations for Bus In/Out Detection in Smartphone-based Surveys—0
EcoFusion: Energy-Aware Adaptive Sensor Fusion for Efficient Autonomous Vehicle Perception—0
A Tutorial on Adversarial Learning Attacks and Countermeasures—0
An Active and Contrastive Learning Framework for Fine-Grained Off-Road Semantic Segmentation—0
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Benchmark Results

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