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 3751–3775 of 6092 papers

TitleStatusHype
Detecting OODs as datapoints with High Uncertainty—0
Detecting the Anomalies in LiDAR Pointcloud—0
Detection Is Tracking: Point Cloud Multi-Sweep Deep Learning Models Revisited—0
Detection of Adversarial Physical Attacks in Time-Series Image Data—0
Detection of Condensed Vehicle Gas Exhaust in LiDAR Point Clouds—0
Detector Collapse: Physical-World Backdooring Object Detection to Catastrophic Overload or Blindness in Autonomous Driving—0
DETR4D: Direct Multi-View 3D Object Detection with Sparse Attention—0
DeTra: A Unified Model for Object Detection and Trajectory Forecasting—0
Developing a Purely Visual Based Obstacle Detection using Inverse Perspective Mapping—0
Development and testing of an image transformer for explainable autonomous driving systems—0
Development of A Stochastic Traffic Environment with Generative Time-Series Models for Improving Generalization Capabilities of Autonomous Driving Agents—0
Development of Occupancy Prediction Algorithm for Underground Parking Lots—0
Development of Open Informal Dataset Affecting Autonomous Driving—0
Development of Real-time Rendering Technology for High-Precision Models in Autonomous Driving—0
DF-Calib: Targetless LiDAR-Camera Calibration via Depth Flow—0
DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control—0
DG-Labeler and DGL-MOTS Dataset: Boost the Autonomous Driving Perception—0
DGNR: Density-Guided Neural Point Rendering of Large Driving Scenes—0
DIAL: Distribution-Informed Adaptive Learning of Multi-Task Constraints for Safety-Critical Systems—0
DICE: Diverse Diffusion Model with Scoring for Trajectory Prediction—0
DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving—0
Differentiable Control Barrier Functions for Vision-based End-to-End Autonomous Driving—0
Differentially Private and Fair Classification via Calibrated Functional Mechanism—0
Differential Transformer-driven 6G Physical Layer for Collaborative Perception Enhancement—0
DiffLO: Semantic-Aware LiDAR Odometry with Diffusion-Based Refinement—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