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 176–200 of 2605 papers

TitleStatusHype
Between Innovation and Oversight: A Cross-Regional Study of AI Risk Management Frameworks in the EU, U.S., UK, and China—0
Automatic Vehicle Detection using DETR: A Transformer-Based Approach for Navigating Treacherous Roads—0
CAML: Collaborative Auxiliary Modality Learning for Multi-Agent Systems—0
A Real-time Spatio-Temporal Trajectory Planner for Autonomous Vehicles with Semantic Graph Optimization—0
IBURD: Image Blending for Underwater Robotic Detection—0
A Multi-Scale Isolation Forest Approach for Real-Time Detection and Filtering of FGSM Adversarial Attacks in Video Streams of Autonomous Vehicles—0
Cross-Model Transferability of Adversarial Patches in Real-time Segmentation for Autonomous DrivingCode0
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments—0
BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory PredictionCode0
Deep learning based infrared small object segmentation: Challenges and future directions—0
Building reliable sim driving agents by scaling self-playCode4
Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration—0
Multi-Objective Reinforcement Learning for Critical Scenario Generation of Autonomous Vehicles—0
Towards Robust and Secure Embodied AI: A Survey on Vulnerabilities and Attacks—0
Collaboration Between the City and Machine Learning Community is Crucial to Efficient Autonomous Vehicles Routing—0
AI Generations: From AI 1.0 to AI 4.0—0
Safe platooning control of connected and autonomous vehicles on curved multi-lane roads—0
V2V-LLM: Vehicle-to-Vehicle Cooperative Autonomous Driving with Multi-Modal Large Language Models—0
Mind the Gaps: Logical English, Prolog, and Multi-agent Systems for Autonomous Vehicles—0
Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception—0
AdvSwap: Covert Adversarial Perturbation with High Frequency Info-swapping for Autonomous Driving Perception—0
Poly-Autoregressive Prediction for Modeling Interactions—0
Predictive Planner for Autonomous Driving with Consistency Models—0
Vision-Language Models for Edge Networks: A Comprehensive Survey—0
Optimal Actuator Attacks on Autonomous Vehicles Using Reinforcement Learning—0
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Benchmark Results

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