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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 941–950 of 2605 papers

TitleStatusHype
Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions using Reinforcement Learning—0
Exploiting latent representation of sparse semantic layers for improved short-term motion prediction with Capsule Networks—0
A Brief Survey on Autonomous Vehicle Possible Attacks, Exploits and Vulnerabilities—0
Exploiting Richness of Learned Compressed Representation of Images for Semantic Segmentation—0
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain—0
Exploration of Reinforcement Learning for Event Camera using Car-like Robots—0
Explore the Use of Time Series Foundation Model for Car-Following Behavior Analysis—0
Exploring Camera Encoder Designs for Autonomous Driving Perception—0
Exploring Driving Behavior for Autonomous Vehicles Based on Gramian Angular Field Vision Transformer—0
Automated design of error-resilient and hardware-efficient deep neural networks—0
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Benchmark Results

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