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 5301–5325 of 6092 papers

TitleStatusHype
Scalable Adversarial Attack on Graph Neural Networks with Alternating Direction Method of Multipliers—0
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition—0
Scalable Decentralized Cooperative Platoon using Multi-Agent Deep Reinforcement Learning—0
Scalable Detection and Tracking of Geometric Extended Objects—0
Scalable Place Recognition Under Appearance Change for Autonomous Driving—0
Scalable Primitives for Generalized Sensor Fusion in Autonomous Vehicles—0
Scaling Is All You Need: Autonomous Driving with JAX-Accelerated Reinforcement Learning—0
Scaling Motion Forecasting Models with Ensemble Distillation—0
SCaRL- A Synthetic Multi-Modal Dataset for Autonomous Driving—0
Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning—0
Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction—0
Scenario Understanding of Traffic Scenes Through Large Visual Language Models—0
Scene-Aware Conversational ADAS with Generative AI for Real-Time Driver Assistance—0
SceneCalib: Automatic Targetless Calibration of Cameras and Lidars in Autonomous Driving—0
Neural Eulerian Scene Flow Fields—0
SceneLLM: Implicit Language Reasoning in LLM for Dynamic Scene Graph Generation—0
Efficient Data Representation for Motion Forecasting: A Scene-Specific Trajectory Set Approach—0
Scene Transformer: A unified architecture for predicting future trajectories of multiple agents—0
Scene Understanding for Autonomous Driving—0
Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System—0
S&CNet: Monocular Depth Completion for Autonomous Systems and 3D Reconstruction—0
SCP: Scene Completion Pre-training for 3D Object Detection—0
SCR-Graph: Spatial-Causal Relationships based Graph Reasoning Network for Human Action Prediction—0
SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs—0
SDGE: Stereo Guided Depth Estimation for 360^ Camera Sets—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