Shaoguang Chen

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hree-dimensional shapes are used extensively in fields such as mechanical design, multimedia games, architecture, and medical diagnosis. 1 All of these applications need to store, recognize , and retrieve 3D models effectively and automatically. Because the characteristics of 3D shapes differ from those of text and images, traditional classification and(More)
Deep learning has emerged as a powerful technique to extract high-level features from low-level information, which shows that hierarchical representation can be easily achieved. However, applying deep learning into 3D shape is still a challenge. In this paper, we propose a novel high-level feature learning method for 3D shape retrieval based on deep(More)
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