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 1021–1030 of 2605 papers

TitleStatusHype
Dynamic and Static Object Detection Considering Fusion Regions and Point-wise Features—0
Dynamically Modulating Visual Place Recognition Sequence Length For Minimum Acceptable Performance Scenarios—0
Beyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles—0
A New Multi-vehicle Trajectory Generator to Simulate Vehicle-to-Vehicle Encounters—0
Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery—0
3D Scene Understanding at Urban Intersection using Stereo Vision and Digital Map—0
Dynamically Local-Enhancement Planner for Large-Scale Autonomous Driving—0
Beyond Empirical Windowing: An Attention-Based Approach for Trust Prediction in Autonomous Vehicles—0
Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentation—0
Dueling Deep Q Network for Highway Decision Making in Autonomous Vehicles: A Case Study—0
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Benchmark Results

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