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 24762500 of 6092 papers

TitleStatusHype
Identifying Unknown Instances for Autonomous Driving0
DeepAVO: Efficient Pose Refining with Feature Distilling for Deep Visual Odometry0
Deep auxiliary learning for visual localization using colorization task0
AutoDrive-QA- Automated Generation of Multiple-Choice Questions for Autonomous Driving Datasets Using Large Vision-Language Models0
Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector0
DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving0
AUTO-DISCERN: Autonomous Driving Using Common Sense Reasoning0
AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents0
Decoupling of neural network calibration measures0
DecoupledGaussian: Object-Scene Decoupling for Physics-Based Interaction0
AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework0
Decoupled Diffusion Sparks Adaptive Scene Generation0
DecoratingFusion: A LiDAR-Camera Fusion Network with the Combination of Point-level and Feature-level Fusion0
Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications0
Uncertainty-Aware DNN for Multi-Modal Camera Localization0
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection0
Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios0
Decoding Interpretable Logic Rules from Neural Networks0
Decoder Fusion RNN: Context and Interaction Aware Decoders for Trajectory Prediction0
AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection0
Robust Evolutionary Multi-Objective Network Architecture Search for Reinforcement Learning (EMNAS-RL)0
Decision-making Strategy on Highway for Autonomous Vehicles using Deep Reinforcement Learning0
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control0
Decision Making for Autonomous Driving in Interactive Merge Scenarios via Learning-based Prediction0
AuthSim: Towards Authentic and Effective Safety-critical Scenario Generation for Autonomous Driving Tests0
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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