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 1976–2000 of 2605 papers

TitleStatusHype
A Dataset for Lane Instance Segmentation in Urban Environments—0
ADCNet: Learning from Raw Radar Data via Distillation—0
Addressing Data Annotation Challenges in Multiple Sensors: A Solution for Scania Collected Datasets—0
Addressing the IEEE AV Test Challenge with Scenic and VerifAI—0
Deep Reinforcement-Learning-based Driving Policy for Autonomous Road Vehicles—0
A Discrete-time Dynamical Model for Optimal Dispatching and Rebalancing of Autonomous Mobility-on-Demand Systems—0
A Distributed Model-Free Algorithm for Multi-hop Ride-sharing using Deep Reinforcement Learning—0
ADoPT: LiDAR Spoofing Attack Detection Based on Point-Level Temporal Consistency—0
A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture—0
A Driving Intention Prediction Method Based on Hidden Markov Model for Autonomous Driving—0
Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery—0
Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection—0
Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap—0
Advantage Alignment Algorithms—0
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction—0
Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions—0
Adversarial 3D Virtual Patches using Integrated Gradients—0
Adversarial Attacks on Camera-LiDAR Models for 3D Car Detection—0
Adversarial Attacks on Convolutional Neural Networks in Facial Recognition Domain—0
Adversarial Attacks on Traffic Sign Recognition: A Survey—0
Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios—0
Adversarial Examples: Opportunities and Challenges—0
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems—0
Adversarial Patterns: Building Robust Android Malware Classifiers—0
Adversarial Plannning—0
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Benchmark Results

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