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 851–860 of 2605 papers

TitleStatusHype
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery—0
CacheMamba: Popularity Prediction for Mobile Edge Caching Networks via Selective State Spaces—0
CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving—0
Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula—0
A machine learning environment for evaluating autonomous driving software—0
DeepLaser: Practical Fault Attack on Deep Neural Networks—0
Emerging AI Security Threats for Autonomous Cars -- Case Studies—0
Empowering Autonomous Driving with Large Language Models: A Safety Perspective—0
Deep Koopman Operator-Informed Safety Command Governor for Autonomous Vehicles—0
Automatic Calibration of Multiple 3D LiDARs in Urban Environments—0
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Benchmark Results

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