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 4276–4300 of 6092 papers

TitleStatusHype
Adversarial Zoom Lens: A Novel Physical-World Attack to DNNs—0
A Novel Algorithm for Exact Concave Hull Extraction—0
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming—0
Multi-level Domain Adaptation for Lane Detection—0
A Safe Control Architecture Based on Robust Model Predictive Control for Autonomous Driving—0
C-SENN: Contrastive Self-Explaining Neural Network—0
Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras—0
Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation—0
A Dynamic Data Driven Approach for Explainable Scene Understanding—0
Opendenselane: A Dense Lidar-Based Dataset for HD Map ConstructionCode0
Diverse Multiple Trajectory Prediction Using a Two-stage Prediction Network Trained with Lane Loss—0
SafeRL-Kit: Evaluating Efficient Reinforcement Learning Methods for Safe Autonomous Driving—0
Level 2 Autonomous Driving on a Single Device: Diving into the Devils of OpenpilotCode0
AI Ethics Issues in Real World: Evidence from AI Incident Database—0
Waymo Open Dataset: Panoramic Video Panoptic Segmentation—0
Mean-Semivariance Policy Optimization via Risk-Averse Reinforcement Learning—0
Asymmetric Dual-Decoder U-Net for Joint Rain and Haze RemovalCode0
Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPUCode0
High-Definition Map Generation Technologies For Autonomous Driving—0
R4D: Utilizing Reference Objects for Long-Range Distance Estimation—0
Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label DiffusionCode0
PixSelect: Less but Reliable Pixels for Accurate and Efficient Localization—0
Narrowing the Coordinate-frame Gap in Behavior Prediction Models: Distillation for Efficient and Accurate Scene-centric Motion Forecasting—0
Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking—0
Pushing the Limits of Learning-based Traversability Analysis for Autonomous Driving on CPU—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