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 4701–4725 of 6092 papers

TitleStatusHype
Convex Online Video Frame Subset Selection using Multiple Criteria for Data Efficient Autonomous Driving—0
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types—0
X-view: Non-egocentric Multi-View 3D Object Detector—0
Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs—0
NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform RepresentationCode1
Learning to Robustly Negotiate Bi-Directional Lane Usage in High-Conflict Driving Scenarios—0
Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy—0
CFPNet: Channel-wise Feature Pyramid for Real-Time Semantic SegmentationCode1
Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-SupervisionCode1
Real-time End-to-End Federated Learning: An Automotive Case Study—0
Learn-to-Race: A Multimodal Control Environment for Autonomous RacingCode1
Multimodal Motion Prediction with Stacked TransformersCode1
Scalable Detection and Tracking of Geometric Extended Objects—0
Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving—0
Deep ROC Analysis and AUC as Balanced Average Accuracy to Improve Model Selection, Understanding and Interpretation—0
A Novel Upsampling and Context Convolution for Image Semantic Segmentation—0
Stereo CenterNet based 3D Object Detection for Autonomous Driving—0
From driving automation systems to autonomous vehicles: clarifying the terminology—0
Video Class Agnostic Segmentation Benchmark for Autonomous DrivingCode1
Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving IntelligenceCode1
Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection—0
Deep Reinforcement Learning-Aided RAN Slicing Enforcement for B5G Latency Sensitive Services—0
Building Safer Autonomous Agents by Leveraging Risky Driving Behavior Knowledge—0
Adversarial Driving: Attacking End-to-End Autonomous DrivingCode1
Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutions—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