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 1971–1980 of 2605 papers

TitleStatusHype
SHARKS: Smart Hacking Approaches for RisK Scanning in Internet-of-Things and Cyber-Physical Systems based on Machine Learning—0
A Hybrid Learner for Simultaneous Localization and Mapping—0
Smart Black Box 2.0: Efficient High-bandwidth Driving Data Collection based on Video Anomalies—0
Spatial-Temporal Consistency Network for Low-Latency Trajectory Forecasting—0
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine TranslationCode0
Low-latency Perception in Off-Road Dynamical Low Visibility EnvironmentsCode0
Limitations of Deep Neural Networks: a discussion of G. Marcus' critical appraisal of deep learning—0
Computer Vision based Accident Detection for Autonomous Vehicles—0
Computer Vision based Animal Collision Avoidance Framework for Autonomous Vehicles—0
Sequential Attacks on Kalman Filter-based Forward Collision Warning Systems—0
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Benchmark Results

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