Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
The idea of computer vision as the Bayesian inverse problem to computer graphics has a long history and an appealing elegance, but it has proved difficult to directly implement. Instead, most vision tasks are approached via complex bottom-up processing pipelines. Here we show that it is possible to...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Neural Information Processing Systems Foundation
2015
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| Online Access: | http://hdl.handle.net/1721.1/93171 https://orcid.org/0000-0002-7077-2765 https://orcid.org/0000-0002-1925-2035 |