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 1476–1500 of 2605 papers

TitleStatusHype
Collective Decision Making using Attractive and Repulsive Forces in Markovian Opinion Dynamics—0
DeeP-LCC: Data-EnablEd Predictive Leading Cruise Control in Mixed Traffic FlowCode1
V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision TransformerCode2
Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-LearningCode0
Improving Urban Mobility: using artificial intelligence and new technologies to connect supply and demand—0
Collaborative Driving: Learning- Aided Joint Topology Formulation and Beamforming—0
How to Learn from Risk: Explicit Risk-Utility Reinforcement Learning for Efficient and Safe Driving Strategies—0
An Introduction to Multi-Agent Reinforcement Learning and Review of its Application to Autonomous Mobility—0
Audiovisual Affect Assessment and Autonomous Automobiles: Applications—0
Grounding Commands for Autonomous Vehicles via Layer Fusion with Region-specific Dynamic Layer Attention—0
Moral Dilemmas for Moral Machines—0
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with TransformersCode2
Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review—0
Reconfigurable Intelligent Surface-Aided Joint Radar and Covert Communications: Fundamentals, Optimization, and Challenges—0
Important Object Identification with Semi-Supervised Learning for Autonomous Driving—0
A Quality Index Metric and Method for Online Self-Assessment of Autonomous Vehicles Sensory Perception—0
Adversarial Patterns: Building Robust Android Malware Classifiers—0
Bilateral Deep Reinforcement Learning Approach for Better-than-human Car Following Model—0
Physical Backdoor Attacks to Lane Detection Systems in Autonomous Driving—0
Self-Supervised Scene Flow Estimation with 4-D Automotive RadarCode1
Explaining RADAR features for detecting spoofing attacks in Connected Autonomous Vehicles—0
Deep Camera Pose Regression Using Pseudo-LiDAR—0
PanoFlow: Learning 360° Optical Flow for Surrounding Temporal UnderstandingCode1
Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature AggregationCode1
RONELDv2: A faster, improved lane tracking method—0
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Benchmark Results

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