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 2451–2500 of 6092 papers

TitleStatusHype
Deep Evaluation Metric: Learning to Evaluate Simulated Radar Point Clouds for Virtual Testing of Autonomous Driving—0
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation—0
Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases—0
AGNES: Abstraction-guided Framework for Deep Neural Networks Security—0
DeepDyve: Dynamic Verification for Deep Neural Networks—0
Automated Augmentation with Reinforcement Learning and GANs for Robust Identification of Traffic Signs using Front Camera Images—0
Deep Dynamics: Vehicle Dynamics Modeling with a Physics-Constrained Neural Network for Autonomous Racing—0
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving—0
Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy—0
Aggregated Sparse Attention for Steering Angle Prediction—0
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation—0
AutoLay: Benchmarking amodal layout estimation for autonomous driving—0
Deep Depth Completion from Extremely Sparse Data: A Survey—0
3D Object Proposals for Accurate Object Class Detection—0
DeepCSHAP: Utilizing Shapley Values to Explain Deep Complex-Valued Neural Networks—0
Deep Continuous Conditional Random Fields with Asymmetric Inter-object Constraints for Online Multi-object Tracking—0
Identifying Out-of-Distribution Samples in Real-Time for Safety-Critical 2D Object Detection with Margin Entropy Loss—0
AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving—0
Deep-BrownConrady: Prediction of Camera Calibration and Distortion Parameters Using Deep Learning and Synthetic Data—0
AgentThink: A Unified Framework for Tool-Augmented Chain-of-Thought Reasoning in Vision-Language Models for Autonomous Driving—0
DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems—0
DeepBbox: Accelerating Precise Ground Truth Generation for Autonomous Driving Datasets—0
AutoEncoding Tree for City Generation and Applications—0
3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds—0
Identifying Reaction-Aware Driving Styles of Stochastic Model Predictive Controlled Vehicles by Inverse Reinforcement Learning—0
Identifying Unknown Instances for Autonomous Driving—0
DeepAVO: Efficient Pose Refining with Feature Distilling for Deep Visual Odometry—0
Deep auxiliary learning for visual localization using colorization task—0
AutoDrive-QA- Automated Generation of Multiple-Choice Questions for Autonomous Driving Datasets Using Large Vision-Language Models—0
Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector—0
DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving—0
AUTO-DISCERN: Autonomous Driving Using Common Sense Reasoning—0
AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents—0
Decoupling of neural network calibration measures—0
DecoupledGaussian: Object-Scene Decoupling for Physics-Based Interaction—0
AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework—0
Decoupled Diffusion Sparks Adaptive Scene Generation—0
DecoratingFusion: A LiDAR-Camera Fusion Network with the Combination of Point-level and Feature-level Fusion—0
Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications—0
Uncertainty-Aware DNN for Multi-Modal Camera Localization—0
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection—0
Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios—0
Decoding Interpretable Logic Rules from Neural Networks—0
Decoder Fusion RNN: Context and Interaction Aware Decoders for Trajectory Prediction—0
AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection—0
Robust Evolutionary Multi-Objective Network Architecture Search for Reinforcement Learning (EMNAS-RL)—0
Decision-making Strategy on Highway for Autonomous Vehicles using Deep Reinforcement Learning—0
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control—0
Decision Making for Autonomous Driving in Interactive Merge Scenarios via Learning-based Prediction—0
AuthSim: Towards Authentic and Effective Safety-critical Scenario Generation for Autonomous Driving Tests—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