Gül Varol, Javier Romero, Xavier Martin, Naureen Mahmood, Michael J. Black...
TL;DR本文提出了使用由 3D 运动捕捉数据生成的合成真实人形图像的大规模数据集 (SURREAL) 来训练卷积神经网络 (CNNs),并且通过该数据集训练的 CNNs 在 RGB 图像中可以准确地进行人物深度估计和人物部分分割。
Abstract
Estimating human pose, shape, and motion from images and videos are
fundamental challenges with many applications. Recent advances in 2D human pose
estimation use large amounts of manually-labeled training data for learning
convolutional neural networks (cnns). Such data is time consum