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 6051–6075 of 6092 papers

TitleStatusHype
LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds—0
Lessons Learned from Accident of Autonomous Vehicle Testing: An Edge Learning-aided Offloading Framework—0
LEST: Large-scale LiDAR Semantic Segmentation with Transformer—0
Let Hybrid A* Path Planner Obey Traffic Rules: A Deep Reinforcement Learning-Based Planning Framework—0
Let Occ Flow: Self-Supervised 3D Occupancy Flow Prediction—0
LeTS-Drive: Driving in a Crowd by Learning from Tree Search—0
Let's Get Dirty: GAN Based Data Augmentation for Camera Lens Soiling Detection in Autonomous Driving—0
LetsMap: Unsupervised Representation Learning for Semantic BEV Mapping—0
Cognitive Level-k Meta-Learning for Safe and Pedestrian-Aware Autonomous Driving—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
Levels of AGI for Operationalizing Progress on the Path to AGI—0
Levels of AI Agents: from Rules to Large Language Models—0
Leveraging Clickstream Trajectories to Reveal Low-Quality Workers in Crowdsourced Forecasting Platforms—0
Leveraging Edge Intelligence and LLMs to Advance 6G-Enabled Internet of Automated Defense Vehicles—0
Leveraging Large Language Models for Enhancing Autonomous Vehicle Perception—0
Leveraging machine learning for less developed languages: Progress on Urdu text detection—0
Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation—0
Leveraging Road Area Semantic Segmentation with Auxiliary Steering Task—0
Leveraging SD Map to Augment HD Map-based Trajectory Prediction—0
Leveraging Stable Diffusion for Monocular Depth Estimation via Image Semantic Encoding—0
Leveraging Temporal Cues for Semi-Supervised Multi-View 3D Object Detection—0
Leveraging the Edge and Cloud for V2X-Based Real-Time Object Detection in Autonomous Driving—0
Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving—0
LFP: Efficient and Accurate End-to-End Lane-Level Planning via Camera-LiDAR Fusion—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