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

Showing 426450 of 6092 papers

TitleStatusHype
DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion modelCode2
RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Learning in Multi-Modal Large Language ModelCode2
FADet: A Multi-sensor 3D Object Detection Network based on Local Featured AttentionCode1
3D Gaussian Splatting against Moving Objects for High-Fidelity Street Scene ReconstructionCode1
Extending Large Vision-Language Model for Diverse Interactive Tasks in Autonomous DrivingCode1
Fast Kernel Scene FlowCode1
Exploring Simple 3D Multi-Object Tracking for Autonomous DrivingCode1
Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with TransformerCode1
Exploring Map-based Features for Efficient Attention-based Vehicle Motion PredictionCode1
Ad-datasets: a meta-collection of data sets for autonomous drivingCode1
Exploring Navigation Maps for Learning-Based Motion PredictionCode1
Exploring the Devil in Graph Spectral Domain for 3D Point Cloud AttacksCode1
FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction FrameworkCode1
Explaining Autonomous Driving Actions with Visual Question AnsweringCode1
Explainable Object-induced Action Decision for Autonomous VehiclesCode1
Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic SegmentationCode1
Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile RobotsCode1
Asynchronous Blob Tracker for Event CamerasCode1
Explainability of Point Cloud Neural Networks Using SMILE: Statistical Model-Agnostic Interpretability with Local ExplanationsCode1
Exploring Attention GAN for Vehicle Motion PredictionCode1
Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch AttacksCode1
Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous VehiclesCode1
Evaluation of Differentially Constrained Motion Models for Graph-Based Trajectory PredictionCode1
A Platform-Agnostic Deep Reinforcement Learning Framework for Effective Sim2Real Transfer towards Autonomous DrivingCode1
1st Place Solution for PVUW Challenge 2023: Video Panoptic SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95Unverified
2InterFuserDriving Score76.18Unverified
3TCPDriving Score75.14Unverified
4TF++ WPDriving Score66.32Unverified
5Learning From All Vehicles (LAV)Driving Score61.85Unverified
6TransFuserDriving Score61.18Unverified
7TransFuser (Reproduced)Driving Score55.04Unverified
8TCP (Reproduced)Driving Score47.91Unverified
9Latent TransFuserDriving Score45.2Unverified
10GRIADDriving Score36.79Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17Unverified
2TransFuserRC56.36Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91Unverified
2TransFuserRC78.41Unverified