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 5476–5500 of 6092 papers

TitleStatusHype
Open-set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic ScenariosCode0
Opendenselane: A Dense Lidar-Based Dataset for HD Map ConstructionCode0
CoMamba: Real-time Cooperative Perception Unlocked with State Space ModelsCode0
H_ Model-free Reinforcement Learning with Robust Stability GuaranteeCode0
Collision Avoidance Metric for 3D Camera EvaluationCode0
Adversarial Mixture Density Networks: Learning to Drive Safely from Collision DataCode0
Adversarial Manhole: Challenging Monocular Depth Estimation and Semantic Segmentation Models with Patch AttackCode0
Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual PatternsCode0
HiLO: High-Level Object Fusion for Autonomous Driving using TransformersCode0
WildRefer: 3D Object Localization in Large-scale Dynamic Scenes with Multi-modal Visual Data and Natural LanguageCode0
seg_3D_by_PC2D: Multi-View Projection for Domain Generalization and Adaptation in 3D Semantic SegmentationCode0
High-Order Evolving Graphs for Enhanced Representation of Traffic DynamicsCode0
SegMap: Segment-based mapping and localization using data-driven descriptorsCode0
On the Road with 16 Neurons: Mental Imagery with Bio-inspired Deep Neural NetworksCode0
HierDAMap: Towards Universal Domain Adaptive BEV Mapping via Hierarchical Perspective PriorsCode0
Dimensionality of datasets in object detection networksCode0
PPO-Based Vehicle Control for Ramp Merging Scheme Assisted by Enhanced C-V2XCode0
On the Importance of Backbone to the Adversarial Robustness of Object DetectorsCode0
Segment-Anything Models Achieve Zero-shot Robustness in Autonomous DrivingCode0
ADM: Accelerated Diffusion Model via Estimated Priors for Robust Motion Prediction under UncertaintiesCode0
On the Fly Neural Style Smoothing for Risk-Averse Domain GeneralizationCode0
Segmenting the FutureCode0
On the Black-box Explainability of Object Detection Models for Safe and Trustworthy Industrial ApplicationsCode0
CollaFuse: Navigating Limited Resources and Privacy in Collaborative Generative AICode0
Hierarchical Deep Stereo Matching on High-resolution ImagesCode0
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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