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

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Showing 4651–4700 of 6092 papers

TitleStatusHype
Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation—0
Understanding Domain Randomization for Sim-to-real Transfer—0
Real-time Nonlinear MPC Strategy with Full Vehicle Validation for Autonomous Driving—0
Hierarchical Potential-based Reward Shaping from Task SpecificationsCode0
3D-FCT: Simultaneous 3D Object Detection and Tracking Using Feature Correlation—0
Reversible Attack based on Local Visual Adversarial Perturbation—0
Deep Instance Segmentation with Automotive Radar Detection Points—0
Influencing Towards Stable Multi-Agent Interactions—0
A Methodology to Identify Cognition Gaps in Visual Recognition Applications Based on Convolutional Neural Networks—0
CertainNet: Sampling-free Uncertainty Estimation for Object Detection—0
Marginally calibrated response distributions for end-to-end learning in autonomous drivingCode0
Cycle-Consistent World Models for Domain Independent Latent Imagination—0
Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning—0
Classification of Time-Series Data Using Boosted Decision TreesCode0
How To Not Drive: Learning Driving Constraints from Demonstration—0
Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation—0
Emergency Vehicles Audio Detection and Localization in Autonomous Driving—0
Transferability Estimation for Semantic Segmentation Task—0
Calibration Regularized Training of Deep Neural Networks using Kernel Density Estimation—0
Fight fire with fire: countering bad shortcuts in imitation learning with good shortcuts—0
Lidar Range Image Compression with Deep Delta Encoding—0
Joint Self-Supervised Learning for Vision-based Reinforcement Learning—0
Scene Transformer: A unified architecture for predicting future trajectories of multiple agents—0
Explanation-Aware Experience Replay in Rule-Dense EnvironmentsCode0
A Step Towards Efficient Evaluation of Complex Perception Tasks in Simulation—0
Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving—0
Up-to-Down Network: Fusing Multi-Scale Context for 3D Semantic Scene Completion—0
Learning Interpretable BEV Based VIO without Deep Neural Networks—0
Automatic Map Update Using Dashcam Videos—0
PredictionNet: Real-Time Joint Probabilistic Traffic Prediction for Planning, Control, and Simulation—0
Towards Generalized and Incremental Few-Shot Object Detection—0
Benchmarking Lane-changing Decision-making for Deep Reinforcement Learning—0
Survey on Semantic Stereo Matching / Semantic Depth Estimation—0
A Distance-based Anomaly Detection Framework for Deep Reinforcement Learning—0
Anomaly Detection in Radar Data Using PointNets—0
Stochastic MPC with Multi-modal Predictions for Traffic Intersections—0
ACReL: Adversarial Conditional value-at-risk Reinforcement Learning—0
Generalized dynamic cognitive hierarchy models for strategic driving behavior—0
Carl-Lead: Lidar-based End-to-End Autonomous Driving with Contrastive Deep Reinforcement Learning—0
METEOR:A Dense, Heterogeneous, and Unstructured Traffic Dataset With Rare Behaviors—0
Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual PatternsCode0
Real Time Monocular Vehicle Velocity Estimation using Synthetic Data—0
Risk Measurement, Risk Entropy, and Autonomous Driving Risk Modeling—0
Neural Architecture Search in operational context: a remote sensing case-study—0
Federated Ensemble Model-based Reinforcement Learning in Edge Computing—0
Residual 3D Scene Flow Learning with Context-Aware Feature Extraction—0
Smart Automotive Technology Adherence to the Law: (De)Constructing Road Rules for Autonomous System Development, Verification and Safety—0
Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks—0
Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models—0
An Efficient Deep Learning Approach Using Improved Generative Adversarial Networks for Incomplete Information Completion of Self-driving—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