DeepCap:一种用于描述黑白图像的深度学习模型

Vaibhav Pandit, Rishabh Gulati, Chaitanya Singla, Sandeep Kr. Singh
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引用次数: 2

摘要

彩色图像的字幕已经存在很长一段时间了,它使用对象检测和对象之间的空间关系来生成字幕。在过去,有许多方法可以为彩色图像添加标题,但很少。在本文中,我们提出了一种方法来说明黑白图像没有任何尝试着色。我们使用迁移学习来实现Inception V3,这是一个由Google开发的CNN模型,也是ImageNet图像分类挑战的亚军,它从黑白图像中生成字幕,在验证集上实现了45.77%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DeepCap: A Deep Learning Model to Caption Black and White Images
Captioning of colored images has been around for quite some time now, it uses object detection and the spatial relation between the objects to generate captions. There have been numerous approaches to caption colorized images in the past, but there have been a very few. In this paper we present an approach to caption Black and white images without any attempt of colorization. We have used transfer learning to implement Inception V3, a CNN model developed by Google and a runner up in the ImageNet image classification challenge, to generate captions from Black and white images achieving an accuracy of 45.77% on the validation set.
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