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 591–600 of 2605 papers

TitleStatusHype
A Comparative Analysis of Machine Learning Methods for Lane Change Intention Recognition Using Vehicle Trajectory Data—0
BEVMOSNet: Multimodal Fusion for BEV Moving Object Segmentation—0
Between Innovation and Oversight: A Cross-Regional Study of AI Risk Management Frameworks in the EU, U.S., UK, and China—0
A New Adversarial Perspective for LiDAR-based 3D Object Detection—0
Benefits of V2V communication in connected and autonomous vehicles in the presence of delays in communicated signals—0
Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators—0
An Evaluation of RGB and LiDAR Fusion for Semantic Segmentation—0
A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture—0
ADoPT: LiDAR Spoofing Attack Detection Based on Point-Level Temporal Consistency—0
A Neurosymbolic Approach to Adaptive Feature Extraction in SLAM—0
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Benchmark Results

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