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 4301–4325 of 6092 papers

TitleStatusHype
Driving in Real Life with Inverse Reinforcement Learning—0
Physics and semantic informed multi-sensor calibration via optimization theory and self-supervised learning—0
Effects of Augmented-Reality-Based Assisting Interfaces on Drivers' Object-wise Situational Awareness in Highly Autonomous Vehicles—0
Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path—0
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving—0
Estimating counterfactual treatment outcomes over time in complex multiagent scenarios—0
RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding—0
StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving—0
Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation ModelsCode0
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems—0
Time3D: End-to-End Joint Monocular 3D Object Detection and Tracking for Autonomous Driving—0
Reinforcement Learning with a TerminatorCode0
Searching for the Essence of Adversarial Perturbations—0
Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehicles—0
BadDet: Backdoor Attacks on Object DetectionCode0
Fault-Aware Design and Training to Enhance DNNs Reliability with Zero-Overhead—0
Risk of Stochastic Systems for Temporal Logic Specifications—0
3D-model ShapeNet Core Classification using Meta-Semantic LearningCode0
Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images—0
Semantic Segmentation for Thermal Images: A Comparative Survey—0
Structure Aware and Class Balanced 3D Object Detection on nuScenes Dataset—0
Collaborative 3D Object Detection for Automatic Vehicle Systems via Learnable Communications—0
Learning to Drive Using Sparse Imitation Reinforcement Learning—0
Towards Model Generalization for Monocular 3D Object Detection—0
Monitoring of Perception Systems: Deterministic, Probabilistic, and Learning-based Fault Detection and IdentificationCode0
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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