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Landmark localization on objects in images using convolutional neural networks

机译:使用卷积神经网络对图像中的对象进行地标定位

摘要

A system and method are provided. The system includes an image capture device configured to capture an actual image depicting an object. The system also includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, a set of synthetic images with corresponding intermediate shape concept labels. The processor is also configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is further configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D geometric structure and a 3D geometric structure of the object depicted in the actual image.
机译:提供了一种系统和方法。该系统包括图像捕获设备,该图像捕获设备被配置为捕获描绘对象的实际图像。该系统还包括处理器。处理器被配置为基于一组3D计算机辅助设计(CAD)模型渲染具有相应中间形状概念标签的一组合成图像。处理器还配置为形成多层卷积神经网络(CNN),该层基于所渲染的合成图像共同对多个中间形状概念进行建模。处理器还被配置为通过将CNN应用于实际图像以输出包括2D几何结构和3D几何结构的图像对,从而对实际图像执行类内外观变化感知和遮挡感知3D对象解析。实际图像中描绘的对象。

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