We present a deep convolutional decoder architecture that can generate volumetric 3D
outputs in a compute-and memory-efficient manner by using an octree representation. The …

In this paper, we propose a novel 3D-RecGAN approach, which reconstructs the complete
3D structure of a given object from a single arbitrary depth view using generative adversarial …

In this paper, we propose a novel approach, 3D-RecGAN++, which reconstructs the
complete 3D structure of a given object from a single arbitrary depth view using generative …

Reconstructing the three-dimensional structure of a scene is a classic and fundamental
problem in computer vision, but it has been revolutionized by recent advancements in deep …

Cardiovascular diseases are the leading cause of death globally and surgical treatments for
these often begin with the manual placement of a long compliant wire, called a guidewire …

Previous 3D object reconstruction methods from 2D images involve two issues: the lack of in-
depth exploration of the prior knowledge of 3D shapes, and the difficulty of dealing with the …

Deep learning for 3D reconstruction have just shown some promising advantanges, where
3D shapes can be predicted from a single RGB image. However, such works are often …

Helmholtz stereopsis is one the versatile techniques for 3D geometry reconstruction from 2D
images of objects with unknown and arbitrary reflectance surfaces. HS eliminates the need …

While recent deep neural networks have achieved promising results for 3D reconstruction
from a single-view image, these rely on the availability of RGB textures in images and extra …

Object reconstruction is one of the most crucial branches of computer vision. With the
development of deep learning, many tasks have achieved remarkable improvements in …