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

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Showing 51–75 of 2605 papers

TitleStatusHype
CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse TransformersCode2
ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous VehiclesCode2
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with TransformersCode2
SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion PredictionCode2
DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam VideosCode2
Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View DatasetsCode2
Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous DrivingCode2
VBR: A Vision Benchmark in RomeCode2
HiVT: Hierarchical Vector Transformer for Multi-Agent Motion PredictionCode2
GSPR: Multimodal Place Recognition Using 3D Gaussian Splatting for Autonomous DrivingCode2
Flow: A Modular Learning Framework for Mixed Autonomy TrafficCode2
OccFusion: Multi-Sensor Fusion Framework for 3D Semantic Occupancy PredictionCode2
Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion TransformerCode2
CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-AttentionCode1
Coupling Intent and Action for Pedestrian Crossing Behavior PredictionCode1
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object DetectionCode1
A Counterfactual Safety Margin Perspective on the Scoring of Autonomous Vehicles' RiskinessCode1
CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement LearningCode1
Counterfactual Multi-Agent Policy GradientsCode1
CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous DrivingCode1
Continuous-Time Spatiotemporal Calibration of a Rolling Shutter Camera---IMU SystemCode1
Continual Driving Policy Optimization with Closed-Loop Individualized CurriculaCode1
COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked VehiclesCode1
Collaborative Motion Prediction via Neural Motion Message PassingCode1
MSMA: Multi-agent Trajectory Prediction in Connected and Autonomous Vehicle Environment with Multi-source Data IntegrationCode1
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Benchmark Results

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