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 951–975 of 2605 papers

TitleStatusHype
Motion planning for off-road autonomous driving based on human-like cognition and weight adaptation—0
Enhancing Track Management Systems with Vehicle-To-Vehicle Enabled Sensor Fusion—0
On the Federated Learning Framework for Cooperative Perception—0
Dense Road Surface Grip Map Prediction from Multimodal Image Data—0
Redefining Safety for Autonomous Vehicles—0
Toward Physics-Aware Deep Learning Architectures for LiDAR Intensity SimulationCode0
Enhancing High-Speed Cruising Performance of Autonomous Vehicles through Integrated Deep Reinforcement Learning Framework—0
ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions—0
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction—0
Optimization-based Heuristic for Vehicle Dynamic Coordination in Mixed Traffic Intersections—0
Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction—0
Collaborative Perception Datasets in Autonomous Driving: A Survey—0
How Real Is Real? A Human Evaluation Framework for Unrestricted Adversarial Examples—0
On-board classification of underwater images using hybrid classical-quantum CNN based method—0
An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehicles—0
S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles—0
Learning a Stable, Safe, Distributed Feedback Controller for a Heterogeneous Platoon of Autonomous Vehicles—0
How to deal with glare for improved perception of Autonomous Vehicles—0
Developing Situational Awareness for Joint Action with Autonomous Vehicles—0
Characterization and Mitigation of Insufficiencies in Automated Driving Systems—0
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator—0
Benefits of V2V communication in connected and autonomous vehicles in the presence of delays in communicated signals—0
Voice-Assisted Real-Time Traffic Sign Recognition System Using Convolutional Neural Network—0
Depth Estimation using Weighted-loss and Transfer Learning—0
Monocular 3D lane detection for Autonomous Driving: Recent Achievements, Challenges, and Outlooks—0
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Benchmark Results

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