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DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimation

2017-08-28Code Available0· sign in to hype

Markus Oberweger, Vincent Lepetit

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Abstract

DeepPrior is a simple approach based on Deep Learning that predicts the joint 3D locations of a hand given a depth map. Since its publication early 2015, it has been outperformed by several impressive works. Here we show that with simple improvements: adding ResNet layers, data augmentation, and better initial hand localization, we achieve better or similar performance than more sophisticated recent methods on the three main benchmarks (NYU, ICVL, MSRA) while keeping the simplicity of the original method. Our new implementation is available at https://github.com/moberweger/deep-prior-pp .

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Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
ICVL HandsDeepPrior++Average 3D Error8.1Unverified
MSRA HandsDeepPrior++Average 3D Error9.5Unverified
NYU HandsDeepPrior++Average 3D Error12.3Unverified

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