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 1931–1940 of 2605 papers

TitleStatusHype
Confidence Calibration with Bounded Error Using Transformations—0
A statistical framework for efficient out of distribution detection in deep neural networks—0
Grounded Relational Inference: Domain Knowledge Driven Explainable Autonomous Driving—0
Portrait Segmentation Using Ensemble of Heterogeneous Deep-Learning Models—0
Adaptable Deformable Convolutions for Semantic Segmentation of Fisheye Images in Autonomous Driving Systems—0
Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking—0
EfficientLPS: Efficient LiDAR Panoptic Segmentation—0
Finding the Gap: Neuromorphic Motion Vision in Cluttered EnvironmentsCode0
Resource allocation in dynamic multiagent systems—0
Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields—0
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Benchmark Results

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