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 1621–1630 of 2605 papers

TitleStatusHype
Optimal Placement of Roadside Infrastructure Sensors towards Safer Autonomous Vehicle Deployments—0
Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning—0
Finite Time Exact Quantized Average Consensus with Limited Resources and Transmission Stopping for Energy-Aware Networks—0
Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation—0
Modeling Interactions of Autonomous Vehicles and Pedestrians with Deep Multi-Agent Reinforcement Learning for Collision Avoidance—0
Model-Based Robust Adaptive Semantic Segmentation—0
Causal Scene BERT: Improving object detection by searching for challenging groups—0
StereoSpike: Depth Learning with a Spiking Neural NetworkCode1
Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving—0
A taxonomy of strategic human interactions in traffic conflicts—0
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Benchmark Results

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