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 3951–3975 of 6092 papers

TitleStatusHype
Landing AI on Networks: An equipment vendor viewpoint on Autonomous Driving Networks—0
Where and What: Driver Attention-based Object DetectionCode0
Toward Policy Explanations for Multi-Agent Reinforcement LearningCode0
Testing predictive automated driving systems: lessons learned and future recommendations—0
Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-Training—0
RealNet: Combining Optimized Object Detection with Information Fusion Depth Estimation Co-Design Method on IoTCode0
Indoor simultaneous localization and mapping based on fringe projection profilometry—0
Lossy compression of matrices by black-box optimisation of mixed integer nonlinear programming—0
CPGNet: Cascade Point-Grid Fusion Network for Real-Time LiDAR Semantic SegmentationCode1
Is Neuron Coverage Needed to Make Person Detection More Robust?—0
Understanding the Domain Gap in LiDAR Object Detection Networks—0
TorchSparse: Efficient Point Cloud Inference EngineCode3
SELMA: SEmantic Large-scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints—0
Sequential Point Clouds: A Survey—0
Importance is in your attention: agent importance prediction for autonomous driving—0
An Efficient Domain-Incremental Learning Approach to Drive in All Weather ConditionsCode1
Dynamic Point Cloud Denoising via Gradient Fields—0
A Practical Cross-Device Federated Learning Framework over 5G Networks—0
UAMD-Net: A Unified Adaptive Multimodal Neural Network for Dense Depth Completion—0
GitNet: Geometric Prior-based Transformation for Birds-Eye-View Segmentation—0
Stress-Testing Point Cloud Registration on Automotive LiDARCode1
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning—0
Safer Autonomous Driving in a Stochastic, Partially-Observable Environment by Hierarchical Contingency Planning—0
End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-agentCode1
DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
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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