BriefGPT.xyz
Aug, 2016
基础回归:通过亮度恒定和运动平滑无监督学习光流
Back to Basics: Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
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Jason J. Yu, Adam W. Harley, Konstantinos G. Derpanis
TL;DR
本文提出了一种无监督的方法,使用组合数据项和空间项的损失函数训练convnets来预测两幅图像之间的光流,并在KITTI数据集上的实验证明了该方法的有效性。
Abstract
Recently, convolutional networks (
convnets
) have proven useful for predicting
optical flow
. Much of this success is predicated on the availability of large datasets that require expensive and involved data acquis
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