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 1776–1800 of 6092 papers

TitleStatusHype
Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography—0
MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes—0
Eidos: Efficient, Imperceptible Adversarial 3D Point Clouds—0
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
Awesome Multi-modal Object TrackingCode5
RoGs: Large Scale Road Surface Reconstruction with Meshgrid GaussianCode2
TS40K: a 3D Point Cloud Dataset of Rural Terrain and Electrical Transmission System—0
Autonomous Algorithm for Training Autonomous Vehicles with Minimal Human Intervention—0
Task-agnostic Decision Transformer for Multi-type Agent Control with Federated Split Training—0
Traffic Scenario Logic: A Spatial-Temporal Logic for Modeling and Reasoning of Urban Traffic ScenariosCode0
RadarOcc: Robust 3D Occupancy Prediction with 4D Imaging RadarCode2
HighwayLLM: Decision-Making and Navigation in Highway Driving with RL-Informed Language Model—0
ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous VehiclesCode2
System Safety Monitoring of Learned Components Using Temporal Metric Forecasting—0
Enhancing Interaction Modeling with Agent Selection and Physical Coefficient for Trajectory Prediction—0
Transparency Distortion Robustness for SOTA Image Segmentation Tasks—0
Mutual Information Analysis in Multimodal Learning Systems—0
CLRKDNet: Speeding up Lane Detection with Knowledge DistillationCode1
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation—0
Stereo-Knowledge Distillation from dpMV to Dual Pixels for Light Field Video Reconstruction—0
Searching Realistic-Looking Adversarial Objects For Autonomous Driving Systems—0
FADet: A Multi-sensor 3D Object Detection Network based on Local Featured AttentionCode1
Generalized Multi-Objective Reinforcement Learning with Envelope Updates in URLLC-enabled Vehicular Networks—0
RuleFuser: An Evidential Bayes Approach for Rule Injection in Imitation Learned Planners and Predictors for Robustness under Distribution Shifts—0
GEOcc: Geometrically Enhanced 3D Occupancy Network with Implicit-Explicit Depth Fusion and Contextual Self-Supervision—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