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 5476–5500 of 6092 papers

TitleStatusHype
FreeSim: Toward Free-viewpoint Camera Simulation in Driving Scenes—0
Freespace Optical Flow Modeling for Automated Driving—0
From 2D to 3D Cognition: A Brief Survey of General World Models—0
From Bird's-Eye to Street View: Crafting Diverse and Condition-Aligned Images with Latent Diffusion Model—0
From Dataset to Real-world: General 3D Object Detection via Generalized Cross-domain Few-shot Learning—0
From driving automation systems to autonomous vehicles: clarifying the terminology—0
From Failures to Fixes: LLM-Driven Scenario Repair for Self-Evolving Autonomous Driving—0
From Model-Based to Data-Driven Simulation: Challenges and Trends in Autonomous Driving—0
From One to Many: Dynamic Cross Attention Networks for LiDAR and Camera Fusion—0
From Simulation to Real World Maneuver Execution using Deep Reinforcement Learning—0
FSF-Net: Enhance 4D Occupancy Forecasting with Coarse BEV Scene Flow for Autonomous Driving—0
FSNet: Redesign Self-Supervised MonoDepth for Full-Scale Depth Prediction for Autonomous Driving—0
FTA generation using GenAI with an Autonomy sensor Usecase—0
FULLER: Unified Multi-modality Multi-task 3D Perception via Multi-level Gradient Calibration—0
Full Surround Monodepth from Multiple Cameras—0
Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images—0
Learning Interpretable BEV Based VIO without Deep Neural Networks—0
FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving—0
Fusing Bird View LIDAR Point Cloud and Front View Camera Image for Deep Object Detection—0
FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Object Detection—0
FusionLoc: Camera-2D LiDAR Fusion Using Multi-Head Self-Attention for End-to-End Serving Robot Relocalization—0
Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection—0
FusionSAM: Latent Space driven Segment Anything Model for Multimodal Fusion and Segmentation—0
Future-Aware Interaction Network For Motion Forecasting—0
Future Does Matter: Boosting 3D Object Detection with Temporal Motion Estimation in Point Cloud Sequences—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