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 1901–1910 of 2605 papers

TitleStatusHype
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 Animal Collision Avoidance Framework for Autonomous Vehicles—0
Computer Vision based Accident Detection for Autonomous Vehicles—0
Sequential Attacks on Kalman Filter-based Forward Collision Warning Systems—0
Practical Auto-Calibration for Spatial Scene-Understanding from Crowdsourced Dashcamera Videos—0
Non-linear State-space Model Identification from Video Data using Deep EncodersCode1
Next Wave Artificial Intelligence: Robust, Explainable, Adaptable, Ethical, and Accountable—0
Artificial Intelligence at the Edge—0
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Benchmark Results

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