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 876–900 of 6092 papers

TitleStatusHype
SemARFlow: Injecting Semantics into Unsupervised Optical Flow Estimation for Autonomous DrivingCode1
RMMDet: Road-Side Multitype and Multigroup Sensor Detection System for Autonomous DrivingCode1
Lifelong-MonoDepth: Lifelong Learning for Multi-Domain Monocular Metric Depth EstimationCode1
TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion PredictionCode1
Traffic Scene Parsing through the TSP6K DatasetCode1
Depth-based 6DoF Object Pose Estimation using Swin TransformerCode1
BSH-Det3D: Improving 3D Object Detection with BEV Shape HeatmapCode1
LODE: Locally Conditioned Eikonal Implicit Scene Completion from Sparse LiDARCode1
LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene ConstraintsCode1
(Re)^2H2O: Autonomous Driving Scenario Generation via Reversely Regularized Hybrid Offline-and-Online Reinforcement LearningCode1
SUPS: A Simulated Underground Parking Scenario Dataset for Autonomous DrivingCode1
Context-Aware Timewise VAEs for Real-Time Vehicle Trajectory PredictionCode1
StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential EquationCode1
When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement LearningCode1
Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban ScenesCode1
Exploring Navigation Maps for Learning-Based Motion PredictionCode1
Video Waterdrop Removal via Spatio-Temporal Fusion in Driving ScenesCode1
Hierarchical Generative Adversarial Imitation Learning with Mid-level Input Generation for Autonomous Driving on Urban EnvironmentsCode1
Perception Datasets for Anomaly Detection in Autonomous Driving: A SurveyCode1
Generating Evidential BEV Maps in Continuous Driving SpaceCode1
Geometric Deep Learning for Autonomous Driving: Unlocking the Power of Graph Neural Networks With CommonRoad-GeometricCode1
An Efficient Convex Hull-based Vehicle Pose Estimation Method for 3D LiDARCode1
Normalizing Flow based Feature Synthesis for Outlier-Aware Object DetectionCode1
Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution DetectionCode1
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World AttacksCode1
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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