Abstract
Reconstruction 3D objects from a single view is an important research direction in computer vision. With the development of deep learning technology, a single-view 3D reconstruction based on deep learning has made remarkable progress in recent years. In reviewing 3D object reconstruction based on deep learning, firstly, the research progress of 3D reconstruction methods based on deep learning is analyzed in detail according to different representations of 3D objects, i.e., point cloud, voxel, and mesh. Secondly, the standard 3D reconstruction datasets and evaluation criteria are summarized. Finally, the challenges of 3D object reconstruction based on deep learning are summarized.
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