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 2901–2925 of 6092 papers

TitleStatusHype
A Study on Quantifying Sim2Real Image Gap in Autonomous Driving Simulations Using Lane Segmentation Attention Map Similarity—0
QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory PredictionCode2
Towards exploring adversarial learning for anomaly detection in complex driving scenes—0
A survey on deep learning approaches for data integration in autonomous driving system—0
MachMap: End-to-End Vectorized Solution for Compact HD-Map ConstructionCode2
Residual Spatial Fusion Network for RGB-Thermal Semantic Segmentation—0
End-to-End Vectorized HD-map Construction with Piecewise Bezier CurveCode2
Towards Better Certified Segmentation via Diffusion ModelsCode0
Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation—0
PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic SegmentationCode1
The 1st-place Solution for CVPR 2023 OpenLane Topology in Autonomous Driving ChallengeCode2
Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?Code1
A9 Intersection Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perception—0
One-Shot Learning of Visual Path Navigation for Autonomous Vehicles—0
Radars for Autonomous Driving: A Review of Deep Learning Methods and Challenges—0
Mixed-ADC Based PMCW MIMO Radar Angle-Doppler Imaging—0
Motion Comfort Optimization for Autonomous Vehicles: Concepts, Methods, and Techniques—0
Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) for comfortable and safe autonomous driving—0
Datasets and Benchmarks for Offline Safe Reinforcement LearningCode2
Neural World Models for Computer Vision—0
Predict to Detect: Prediction-guided 3D Object Detection using Sequential ImagesCode1
Curricular Subgoals for Inverse Reinforcement LearningCode1
MapSeg: Segmentation guided structured model for online HD map construction—0
Using Collision Momentum in Deep Reinforcement Learning Based Adversarial Pedestrian Modeling—0
LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point CloudsCode0
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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