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 5976–6000 of 6092 papers

TitleStatusHype
3DLaneNAS: Neural Architecture Search for Accurate and Light-Weight 3D Lane DetectionCode0
BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselineCode0
Visual-based Autonomous Driving Deployment from a Stochastic and Uncertainty-aware PerspectiveCode0
Inverse Reinforcement Learning in Contextual MDPsCode0
STONE: A Submodular Optimization Framework for Active 3D Object DetectionCode0
RRPN: Radar Region Proposal Network for Object Detection in Autonomous VehiclesCode0
Towards Pragmatic Semantic Image Synthesis for Urban ScenesCode0
End-to-End Autonomous Driving without Costly Modularization and 3D Manual AnnotationCode0
Straight to Shapes++: Real-time Instance Segmentation Made More AccurateCode0
EMT: A Visual Multi-Task Benchmark Dataset for Autonomous Driving in the Arab Gulf RegionCode0
Streaming Detection of Queried Event StartCode0
Interpretable Safety Validation for Autonomous VehiclesCode0
MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point CloudsCode0
Ego-Motion Aware Target Prediction Module for Robust Multi-Object TrackingCode0
Interpretable ML for Imbalanced DataCode0
R-TOD: Real-Time Object Detector with Minimized End-to-End Delay for Autonomous DrivingCode0
Intention-Aware Control Based on Belief-Space Specifications and Stochastic ExpansionCode0
RTSeg: Real-time Semantic Segmentation Comparative StudyCode0
Effortless Deep Training for Traffic Sign Detection Using Templates and Arbitrary Natural ImagesCode0
Efficient Formal Safety Analysis of Neural NetworksCode0
BEV-LaneDet: An Efficient 3D Lane Detection Based on Virtual Camera via Key-PointsCode0
Instance Segmentation by Deep ColoringCode0
BEVal: A Cross-dataset Evaluation Study of BEV Segmentation Models for Autonomous DrivingCode0
Continual Learning of Unsupervised Monocular Depth from VideosCode0
UniVision: A Unified Framework for Vision-Centric 3D PerceptionCode0
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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