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 4601–4625 of 6092 papers

TitleStatusHype
UdeerLID+: Integrating LiDAR, Image, and Relative Depth with Semi-Supervised—0
UFO: Unidentified Foreground Object Detection in 3D Point Cloud—0
UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving—0
Uncertain Multi-Objective Recommendation via Orthogonal Meta-Learning Enhanced Bayesian Optimization—0
Uncertainty and Self-Supervision in Single-View Depth—0
Uncertainty-Aware Data Aggregation for Deep Imitation Learning—0
Uncertainty-Aware Decision Transformer for Stochastic Driving Environments—0
Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation—0
Uncertainty-Aware Model-Based Reinforcement Learning with Application to Autonomous Driving—0
Uncertainty Aware Proposal Segmentation for Unknown Object Detection—0
Uncertainty-aware Vision-based Metric Cross-view Geolocalization—0
Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving—0
Uncertainty Estimation based on Geometric Separation—0
Uncertainty-Estimation with Normalized Logits for Out-of-Distribution Detection—0
Uncertainty Guided Depth Fusion for Spike Camera—0
Uncertainty-Guided Never-Ending Learning to Drive—0
Uncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks—0
Uncertainty Quantification for Collaborative Object Detection Under Adversarial Attacks—0
Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities—0
Uncertainty Quantification via Neural Posterior Principal Components—0
Emergent Visual Sensors for Autonomous Vehicles—0
Uncovering the human motion pattern: Pattern Memory-based Diffusion Model for Trajectory Prediction—0
UNCOVER: Unknown Class Object Detection for Autonomous Vehicles in Real-time—0
Can't Slow me Down: Learning Robust and Hardware-Adaptive Object Detectors against Latency Attacks for Edge Devices—0
Understanding Domain Randomization for Sim-to-real Transfer—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