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 3726–3750 of 6092 papers

TitleStatusHype
A Lightweight Machine Learning Pipeline for LiDAR-simulation—0
IPDAE: Improved Patch-Based Deep Autoencoder for Lossy Point Cloud Geometry CompressionCode1
Safe and Human-Like Autonomous Driving: A Predictor-Corrector Potential Game Approach—0
TransPillars: Coarse-to-Fine Aggregation for Multi-Frame 3D Object Detection—0
LaneSNNs: Spiking Neural Networks for Lane Detection on the Loihi Neuromorphic Processor—0
Reinforcement Learning for Joint V2I Network Selection and Autonomous Driving Policies—0
ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent QueriesCode1
Time-Dependent Performance Modeling for Platooning Communications at Intersection—0
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions—0
STrajNet: Multi-modal Hierarchical Transformer for Occupancy Flow Field Prediction in Autonomous DrivingCode1
enpheeph: A Fault Injection Framework for Spiking and Compressed Deep Neural NetworksCode0
Robust Trajectory Prediction against Adversarial Attacks—0
Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion TransformerCode2
GPS-GLASS: Learning Nighttime Semantic Segmentation Using Daytime Video and GPS dataCode1
PointFix: Learning to Fix Domain Bias for Robust Online Stereo AdaptationCode0
Semantic Segmentation for Autonomous Driving: Model Evaluation, Dataset Generation, Perspective Comparison, and Real-Time CapabilityCode0
CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous DrivingCode1
Semi-supervised 3D Object Detection with Proficient TeachersCode1
Inter-Frame Compression for Dynamic Point Cloud Geometry Coding—0
p-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations—0
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery—0
Driver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous DrivingCode1
Provable Defense Against Geometric TransformationsCode0
Towards Robust On-Ramp Merging via Augmented Multimodal Reinforcement Learning—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