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 4101–4125 of 6092 papers

TitleStatusHype
Can Deep Learning be Applied to Model-Based Multi-Object Tracking?Code1
360 Depth Estimation in the Wild -- The Depth360 Dataset and the SegFuse NetworkCode1
Sim-to-Real Domain Adaptation for Lane Detection and Classification in Autonomous DrivingCode1
Exploring the Devil in Graph Spectral Domain for 3D Point Cloud AttacksCode1
Memory Replay with Data Compression for Continual LearningCode1
COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasetsCode0
Beyond NaN: Resiliency of Optimization Layers in The Face of InfeasibilityCode0
Motion Sickness Modeling with Visual Vertical Estimation and Its Application to Autonomous Personal Mobility VehiclesCode0
Infrastructure-enabled GPS Spoofing Detection and Correction—0
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving ScenariosCode1
Indy Autonomous Challenge -- Autonomous Race Cars at the Handling Limits—0
Are Transformers More Robust? Towards Exact Robustness Verification for Transformers—0
HALS: A Height-Aware Lidar Super-Resolution Framework for Autonomous Driving—0
Quantification of Actual Road User Behavior on the Basis of Given Traffic RulesCode0
3D Object Detection from Images for Autonomous Driving: A SurveyCode1
Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components—0
Integrated Multiscale Domain Adaptive YOLO—0
Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera IntrinsicsCode1
LiDAR dataset distillation within bayesian active learning framework: Understanding the effect of data augmentation—0
Simulation-to-Reality domain adaptation for offline 3D object annotation on pointclouds with correlation alignment—0
Formal Certification Methods for Automated Vehicle Safety Assessment—0
Multi-modal Sensor Fusion for Auto Driving Perception: A Survey—0
Fast-Spherical-Projection-Based Point Cloud Clustering Algorithm—0
Temporal Robustness of Stochastic SignalsCode0
Learning Interpretable, High-Performing Policies for Autonomous DrivingCode1
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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