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 1161–1170 of 2605 papers

TitleStatusHype
An Active and Contrastive Learning Framework for Fine-Grained Off-Road Semantic Segmentation—0
DepthNet Nano: A Highly Compact Self-Normalizing Neural Network for Monocular Depth Estimation—0
Depth Estimation using Weighted-loss and Transfer Learning—0
Autonomous Vehicle Fleet Coordination With Deep Reinforcement Learning—0
Dependency-Aware CAV Task Scheduling via Diffusion-Based Reinforcement Learning—0
Autonomous Vehicle Decision-Making Framework for Considering Malicious Behavior at Unsignalized Intersections—0
An Accelerated Approach to Safely and Efficiently Test Pre-Production Autonomous Vehicles on Public Streets—0
A Dataset for Lane Instance Segmentation in Urban Environments—0
Acceleration method for generating perception failure scenarios based on editing Markov process—0
Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors—0
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Benchmark Results

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