Multi-View Image Reconstruction Algorithm Based on Virtual Reality Technology

Xiaobing Liao, Liping Wu
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Abstract

In this paper, dense convolutional self-coding block is proposed to extract multi-scale spatial features, and three connection modes are designed to realize feature reuse: intra-unit jump connection and inter-unit dense connection to realize short-term feature reuse mechanism; The inter-block hop connection realizes the long-term feature reuse mechanism. In this paper, a deep convolutional neural network for image super-resolution reconstruction is constructed based on dense convolutional self-coding block, and the network parameters are reduced through multi-scale supervised training, further improving the image reconstruction quality.
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基于虚拟现实技术的多视点图像重建算法
本文提出了密集卷积自编码块提取多尺度空间特征,并设计了三种连接方式实现特征重用:单元内跳转连接和单元间密集连接,实现短期特征重用机制;块间跳连接实现了长期的特征重用机制。本文基于密集卷积自编码块构建了用于图像超分辨率重建的深度卷积神经网络,并通过多尺度监督训练对网络参数进行约简,进一步提高了图像重建质量。
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