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 1951–2000 of 2605 papers

TitleStatusHype
Non-Linear Estimation using the Weighted Average Consensus-Based Unscented Filtering for Various Vehicles Dynamics towards Autonomous Sensorless Design—0
Non-line-of-sight Imaging with Partial Occluders and Surface Normals—0
Novel Actor-Critic Algorithm for Robust Decision Making of CAV under Delays and Loss of V2X Data—0
NovelGym: A Flexible Ecosystem for Hybrid Planning and Learning Agents Designed for Open Worlds—0
NVAutoNet: Fast and Accurate 360^ 3D Visual Perception For Self Driving—0
NVRadarNet: Real-Time Radar Obstacle and Free Space Detection for Autonomous Driving—0
Object detection in adverse weather conditions for autonomous vehicles using Instruct Pix2Pix—0
Object Detection in Autonomous Vehicles: Status and Open Challenges—0
Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques—0
ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data—0
Object Removal Attacks on LiDAR-based 3D Object Detectors—0
Object Scene Flow for Autonomous Vehicles—0
Object Tracking in a 360^o View: A Novel Perspective on Bridging the Gap to Biomedical Advancements—0
Object Viewpoint Classification Based 3D Bounding Box Estimation for Autonomous Vehicles—0
Observability of the relative motion from inertial data in kinematic chains—0
Obstacle Avoidance of Autonomous Vehicles: An LPVMPC with Scheduling Trust Region—0
OccupancyDETR: Using DETR for Mixed Dense-sparse 3D Occupancy Prediction—0
Offline Reinforcement Learning using Human-Aligned Reward Labeling for Autonomous Emergency Braking in Occluded Pedestrian Crossing—0
Off-road Autonomous Vehicles Traversability Analysis and Trajectory Planning Based on Deep Inverse Reinforcement Learning—0
On Addressing Heterogeneity in Federated Learning for Autonomous Vehicles Connected to a Drone Orchestrator—0
On Assessing The Safety of Reinforcement Learning algorithms Using Formal Methods—0
On-board classification of underwater images using hybrid classical-quantum CNN based method—0
On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validation—0
On Deep Learning Techniques to Boost Monocular Depth Estimation for Autonomous Navigation—0
One-Shot Learning of Visual Path Navigation for Autonomous Vehicles—0
OneTrack-M: A multitask approach to transformer-based MOT models—0
Online Adaptation of Neural Network Models by Modified Extended Kalman Filter for Customizable and Transferable Driving Behavior Prediction—0
FuzzRisk: Online Collision Risk Estimation for Autonomous Vehicles based on Depth-Aware Object Detection via Fuzzy Inference—0
Online Predictive Optimization Framework for Stochastic Demand-Responsive Transit Services—0
Online Inference and Detection of Curbs in Partially Occluded Scenes with Sparse LIDAR—0
Online Parameter Estimation for Human Driver Behavior Prediction—0
Online Risk-Bounded Motion Planning for Autonomous Vehicles in Dynamic Environments—0
Online Robust MPC based Emergency Maneuvering System for Autonomous Vehicles—0
On Multi-Agent Deep Deterministic Policy Gradients and their Explainability for SMARTS Environment—0
On the Benefits of Instance Decomposition in Video Prediction Models—0
On the Design of Resilient Distributed Single Time-Scale Estimators: A Graph-Theoretic Approach—0
On the Federated Learning Framework for Cooperative Perception—0
On the Forward Invariance of Neural ODEs—0
On the Impact of CDL and TDL Augmentation for RF Fingerprinting under Impaired Channels—0
On the Metrics for Evaluating Monocular Depth Estimation—0
On the Natural Robustness of Vision-Language Models Against Visual Perception Attacks in Autonomous Driving—0
On the Need for a Statistical Foundation in Scenario-Based Testing of Autonomous Vehicles—0
On Privacy, Security, and Trustworthiness in Distributed Wireless Large AI Models (WLAM)—0
On the Robustness of Segment Anything—0
PEM: Perception Error Model for Virtual Testing of Autonomous Vehicles—0
On the utilization of Macroscopic Information for String Stability of a Vehicular Platoon—0
On Transferability of Driver Observation Models from Simulated to Real Environments in Autonomous Cars—0
Open-Set LiDAR Panoptic Segmentation Guided by Uncertainty-Aware Learning—0
Open vs Closed-ended questions in attitudinal surveys -- comparing, combining, and interpreting using natural language processing—0
Open-World Panoptic Segmentation—0
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Benchmark Results

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