SOTAVerified

Autonomous Driving

Autonomous driving is the task of driving a vehicle 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: Exploring the Limitations of Behavior Cloning for Autonomous Driving)

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5126–5150 of 6092 papers

TitleStatusHype
A Closed-Loop System for Improving Annotation Quality and Efficiency—0
DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAM—0
Automotive Radar Interference Mitigation with Unfolded Robust PCA based on Residual Overcomplete Auto-Encoder Blocks—0
Development of Open Informal Dataset Affecting Autonomous Driving—0
Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications—0
Resource Allocation Complexity Analysis for Relay-based Multihop V2V Communication—0
Hierarchical Attention Learning of Scene Flow in 3D Point Clouds—0
Continuous Safety Verification of Neural Networks—0
Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers—0
Pedestrian Trajectory Prediction with Convolutional Neural Networks—0
Investigating the Robustness of Artificial Intelligent Algorithms with Mixture Experiments—0
Understanding Local Robustness of Deep Neural Networks under Natural VariationsCode0
CurbScan: Curb Detection and Tracking Using Multi-Sensor Fusion—0
Double Targeted Universal Adversarial PerturbationsCode0
Ford Highway Driving RTK Dataset: 30,000 km of North American Highways—0
Multi-Loss Sub-Ensembles for Accurate Classification with Uncertainty Estimation—0
Automotive Radar Data Acquisition using Object DetectionCode0
PrognoseNet: A Generative Probabilistic Framework for Multimodal Position Prediction given Context Information—0
MADRaS : Multi Agent Driving Simulator—0
Lane Change For System-Driven Vehicles Using Dynamic Information—0
Perceptual Modelling of Unconstrained Road Traffic Scenarios with Deep Learning—0
Perceptual Modelling of Unconstrained Road Traffic Scenarios with Deep Learning—0
Bridging the gap between Markowitz planning and deep reinforcement learning—0
Perceptual Modelling of Unconstrained Road Traffic Scenarios with Deep Learning—0
On The Adversarial Robustness of 3D Point Cloud Classification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95—Unverified
2InterFuserDriving Score76.18—Unverified
3TCPDriving Score75.14—Unverified
4TF++ WPDriving Score66.32—Unverified
5Learning From All Vehicles (LAV)Driving Score61.85—Unverified
6TransFuserDriving Score61.18—Unverified
7TransFuser (Reproduced)Driving Score55.04—Unverified
8TCP (Reproduced)Driving Score47.91—Unverified
9Latent TransFuserDriving Score45.2—Unverified
10GRIADDriving Score36.79—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17—Unverified
2TransFuserRC56.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91—Unverified
2TransFuserRC78.41—Unverified