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 91–100 of 2605 papers

TitleStatusHype
CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy TrafficCode1
Continuous-Time Spatiotemporal Calibration of a Rolling Shutter Camera---IMU SystemCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Collaborative Motion Prediction via Neural Motion Message PassingCode1
Bridging Spectral-wise and Multi-spectral Depth Estimation via Geometry-guided Contrastive LearningCode1
Adversarial Example Detection for DNN Models: A Review and Experimental ComparisonCode1
CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-AttentionCode1
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object DetectionCode1
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