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 126–150 of 2605 papers

TitleStatusHype
GndNet: Fast Ground Plane Estimation and Point Cloud Segmentation for Autonomous VehiclesCode1
3DMOTFormer: Graph Transformer for Online 3D Multi-Object TrackingCode1
Deep Reinforcement Learning for Time Allocation and Directional Transmission in Joint Radar-CommunicationCode1
Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive EnvironmentsCode1
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road ScenesCode1
DeeP-LCC: Data-EnablEd Predictive Leading Cruise Control in Mixed Traffic FlowCode1
CVTNet: A Cross-View Transformer Network for Place Recognition Using LiDAR DataCode1
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic SegmentationCode1
Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed TrafficCode1
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object DetectionCode1
CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-AttentionCode1
CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous DrivingCode1
Counterfactual Multi-Agent Policy GradientsCode1
Coupling Intent and Action for Pedestrian Crossing Behavior PredictionCode1
CSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving ScenesCode1
Deep Reinforcement Learning for Human-Like Driving Policies in Collision Avoidance Tasks of Self-Driving CarsCode1
Dolphins: Multimodal Language Model for DrivingCode1
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy FeaturesCode1
Continual Driving Policy Optimization with Closed-Loop Individualized CurriculaCode1
Continuous-Time Spatiotemporal Calibration of a Rolling Shutter Camera---IMU SystemCode1
Collaborative Motion Prediction via Neural Motion Message PassingCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy TrafficCode1
COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked VehiclesCode1
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud DataCode1
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Benchmark Results

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