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 851–875 of 2605 papers

TitleStatusHype
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery—0
CacheMamba: Popularity Prediction for Mobile Edge Caching Networks via Selective State Spaces—0
CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving—0
Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula—0
Automatic driving lane change safety prediction model based on LSTM—0
A machine learning environment for evaluating autonomous driving software—0
Emerging AI Security Threats for Autonomous Cars -- Case Studies—0
Empowering Autonomous Driving with Large Language Models: A Safety Perspective—0
DeepLaser: Practical Fault Attack on Deep Neural Networks—0
Encoding Motion Primitives for Autonomous Vehicles using Virtual Velocity Constraints and Neural Network Scheduling—0
End-to-End 3D Object Detection using LiDAR Point Cloud—0
End-to-End Deep Learning for Steering Autonomous Vehicles Considering Temporal Dependencies—0
End-to-end Evaluation of Practical Video Analytics Systems for Face Detection and Recognition—0
Deep Koopman Operator-Informed Safety Command Governor for Autonomous Vehicles—0
Camera-Radar Perception for Autonomous Vehicles and ADAS: Concepts, Datasets and Metrics—0
End-to-End Lidar-Camera Self-Calibration for Autonomous Vehicles—0
Predictive Planner for Autonomous Driving with Consistency Models—0
End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning—0
End-to-End Steering for Autonomous Vehicles via Conditional Imitation Co-Learning—0
End-to-end Uncertainty-based Mitigation of Adversarial Attacks to Automated Lane Centering—0
Automatic Calibration of Multiple 3D LiDARs in Urban Environments—0
DeepiSign: Invisible Fragile Watermark to Protect the Integrityand Authenticity of CNN—0
Energy-Based Models for Cross-Modal Localization using Convolutional Transformers—0
Can CAV Reduce Non-Recurrent Urban Road Congestion?—0
DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior—0
Show:102550
← PrevPage 35 of 105Next →

Benchmark Results

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