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 5201–5225 of 6092 papers

TitleStatusHype
DAWN: Vehicle Detection in Adverse Weather Nature Dataset—0
Balanced Depth Completion between Dense Depth Inference and Sparse Range Measurements via KISS-GP—0
Reinforced Wasserstein Training for Severity-Aware Semantic Segmentation in Autonomous Driving—0
Measures of Complexity for Large Scale Image Datasets—0
Rethinking 3D LiDAR Point Cloud SegmentationCode0
Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty—0
Robot Action Selection Learning via Layered Dimension Informed Program SynthesisCode0
SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation Synergized with Semantic Segmentation for Autonomous Driving—0
LiDAR Data Enrichment Using Deep Learning Based on High-Resolution Image: An Approach to Achieve High-Performance LiDAR SLAM Using Low-cost LiDAR—0
A Sensitivity Analysis Approach for Evaluating a Radar Simulation for Virtual Testing of Autonomous Driving Functions—0
Graph Signal Processing for Geometric Data and Beyond: Theory and Applications—0
Active Perception using Light Curtains for Autonomous Driving—0
Comparison of Source Coding Techniques for the Vehicle to Vehicle Communication—0
A Comparative Analysis of Deep Reinforcement Learning-enabled Freeway Decision-making for Automated Vehicles—0
PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving—0
Conditional Latent Block Model: a Multivariate Time Series Clustering Approach for Autonomous Driving ValidationCode0
Edge Computing for Real-Time Near-Crash Detection for Smart Transportation Applications—0
Distance-Normalized Unified Representation for Monocular 3D Object Detection—0
PanoNet: Real-time Panoptic Segmentation through Position-Sensitive Feature Embedding—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
Polynomial Regression Network for Variable-Number Lane Detection—0
Modeling the Effects of Windshield Refraction for Camera Calibration—0
Deep Material Recognition in Light-Fields via Disentanglement of Spatial and Angular Information—0
S³Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data—0
Learning to Rank for Active Learning: A Listwise Approach—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