Asymmetric Two-Stream Architecture for Accurate RGB-D Saliency Detection学习笔记

一、背景

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1.对某些复杂情况的RGB图像特征难以鉴别。

appearance features in RGB data are less predictive to some challenging scenes

2.由于RGB图像的复杂特征使用对称两步流模型会“overlooked”，从而产生大量损失。

a symmetric two-stream network may overlook the inherent differences of RGB and depth data.

existing RGB-D methods inevitably suffer from detail information loss [41,16] for adopting strides and pooling operations in the RGB and depth streams.

3.现有的解决方案限制预测特征结构和细节。

An intuitive solution is to use skip-connections [22] or short-connections [21] for reconstructing the detail information.Although these strategies have brought satisfactory improvements, they remain restrictive to predict the complete structures with fine details.

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二.本文要解决的问题

1.有效提取全局信息并且保留局部细节。
2.使用深度特征引导RGB特征精准定位显著目标。

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