Volume: 3D reconstruction of history for immersive platforms

By Or Fleisher, Shirin Anlen. SIGGRAPH Posters, 2018

1,365 citations recorded by the source corpus.

This paper presents Volume, a software toolkit that enables users to experiment with expressive reconstructions of archival and/or historical materials as volumetric renderings. Making use of contemporary deep learning methods, Volume re-imagines 2D images as volumetric 3D assets. These assets can then be incorporated into virtual, augmented and mixed reality experiences.

Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Geology

View Paper: https://www.semanticscholar.org/paper/8b7157531c17d91a4ade28ebc5185e418faee7a7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Graphics and Computer-Aided Design

1. O. Al-Amoudi
2. H. M. Al-Hashemi
3. Yuan Yao
4. Budi Zhao
5. Jianfeng Wang

In Computer Vision and Pattern Recognition

1. Maosong Sun
2. M. Zhou
3. Zhiyuan Liu
4. Ryan Cotterell
5. Mrinmaya Sachan
6. Paris Perdikaris
7. Xu Han
8. Dongdong Zhang

In Geology

1. O. Al-Amoudi
2. H. M. Al-Hashemi

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• A Gentle Introduction to Deep Learning in Medical Image Processing (2018, background): “An excellent overview is given in [37].”