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

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Showing 2901–2950 of 6092 papers

TitleStatusHype
QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory PredictionCode2
A Study on Quantifying Sim2Real Image Gap in Autonomous Driving Simulations Using Lane Segmentation Attention Map Similarity—0
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
PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic SegmentationCode1
End-to-End Vectorized HD-map Construction with Piecewise Bezier CurveCode2
Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation—0
The 1st-place Solution for CVPR 2023 OpenLane Topology in Autonomous Driving ChallengeCode2
Towards Better Certified Segmentation via Diffusion ModelsCode0
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
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
One-Shot Learning of Visual Path Navigation for Autonomous Vehicles—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
LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point CloudsCode0
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory ManagementCode1
Hidden Biases of End-to-End Driving ModelsCode2
Using Collision Momentum in Deep Reinforcement Learning Based Adversarial Pedestrian Modeling—0
Towards a Robust Sensor Fusion Step for 3D Object Detection on Corrupted DataCode0
Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous DrivingCode1
Precise and Generalized Robustness Certification for Neural NetworksCode1
Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI—0
TrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory HypothesesCode1
Self-Interpretable Time Series Prediction with Counterfactual Explanations—0
StreetSurf: Extending Multi-view Implicit Surface Reconstruction to Street ViewsCode2
An Efficient Transformer for Simultaneous Learning of BEV and Lane Representations in 3D Lane Detection—0
A Dynamic Feature Interaction Framework for Multi-task Visual Perception—0
4D Millimeter-Wave Radar in Autonomous Driving: A Survey—0
1st Place Solution for PVUW Challenge 2023: Video Panoptic SegmentationCode1
ICON^2: Reliably Benchmarking Predictive Inequity in Object Detection—0
NeMO: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark—0
Bridging the Gap Between Multi-Step and One-Shot Trajectory Prediction via Self-Supervision—0
Boosting Offline Reinforcement Learning with Action Preference Query—0
X-Align++: cross-modal cross-view alignment for Bird's-eye-view segmentation—0
DVIS: Decoupled Video Instance Segmentation FrameworkCode1
SDR-GAIN: A High Real-Time Occluded Pedestrian Pose Completion Method for Autonomous Driving—0
DeltaNN: Assessing the Impact of Computational Environment Parameters on the Performance of Image Recognition ModelsCode0
Confidence-based federated distillation for vision-based lane-centering—0
Risk-Aware Reward Shaping of Reinforcement Learning Agents for Autonomous DrivingCode0
Mitigating Backdoor Attack Via Prerequisite Transformation—0
Milestones in Autonomous Driving and Intelligent Vehicles Part II: Perception and Planning—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