SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself 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: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 731–740 of 2605 papers

TitleStatusHype
Diffusion-Based Particle-DETR for BEV Perception—0
Digital Twins and Testbeds for Supporting AI Research with Autonomous Vehicle Networks—0
Analyze Drivers' Intervention Behavior During Autonomous Driving -- A VR-incorporated Approach—0
DeepPoint: A Deep Learning Model for 3D Reconstruction in Point Clouds via mmWave Radar—0
Deep Occupancy-Predictive Representations for Autonomous Driving—0
DISC: Dataset for Analyzing Driving Styles In Simulated Crashes for Mixed Autonomy—0
Discovering Avoidable Planner Failures of Autonomous Vehicles using Counterfactual Analysis in Behaviorally Diverse Simulation—0
Discrete Contrastive Learning for Diffusion Policies in Autonomous Driving—0
Autonomous Braking and Throttle System: A Deep Reinforcement Learning Approach for Naturalistic Driving—0
Deep Neural Networks with Koopman Operators for Modeling and Control of Autonomous Vehicles—0
Show:102550
← PrevPage 74 of 261Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified