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 826–850 of 2605 papers

TitleStatusHype
Coherence Awareness in Diffractive Neural NetworksCode0
MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection—0
Mitigating Metropolitan Carbon Emissions with Dynamic Eco-driving at Scale—0
A Recurrent YOLOv8-based framework for Event-Based Object Detection—0
AI and Machine Learning Driven Indoor Localization and Navigation with Mobile Embedded Systems—0
Modeling Electromagnetic Signal Injection Attacks on Camera-based Smart Systems: Applications and Mitigation—0
AgentsCoMerge: Large Language Model Empowered Collaborative Decision Making for Ramp Merging—0
Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors—0
Cross-cultural analysis of pedestrian group behaviour influence on crossing decisions in interactions with autonomous vehicles—0
Communication-Aware Consistent Edge Selection for Mobile Users and Autonomous Vehicles—0
A Survey and Evaluation of Adversarial Attacks for Object Detection—0
Leveraging GNSS and Onboard Visual Data from Consumer Vehicles for Robust Road Network Estimation—0
TransRx-6G-V2X : Transformer Encoder-Based Deep Neural Receiver For Next Generation of Cellular Vehicular Communications—0
Areas of Improvement for Autonomous Vehicles: A Machine Learning Analysis of Disengagement Reports—0
Self-supervised Multi-future Occupancy Forecasting for Autonomous Driving—0
Pixel-Level GPS Localization and Denoising using Computer Vision and 6G Communication Beams—0
Large Language Models for Human-like Autonomous Driving: A Survey—0
RePLAy: Remove Projective LiDAR Depthmap Artifacts via Exploiting Epipolar Geometry—0
Adaptive Target Tracking Using Retrospective Cost Input Estimation—0
FH-DRL: Exponential-Hyperbolic Frontier Heuristics with DRL for accelerated Exploration in Unknown Environments—0
Personalized and Context-aware Route Planning for Edge-assisted Vehicles—0
CRASH: Crash Recognition and Anticipation System Harnessing with Context-Aware and Temporal Focus Attentions—0
CityX: Controllable Procedural Content Generation for Unbounded 3D Cities—0
DVPE: Divided View Position Embedding for Multi-View 3D Object DetectionCode0
Testing Large Language Models on Driving Theory Knowledge and Skills for Connected Autonomous Vehicles—0
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Benchmark Results

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