Systems and methods for providing convolutional neural network based image synthesis using stable and controllable parametric models, a multiscale synthesis framework and novel network architectures
Number of patents in Portfolio can not be more than 2000
United States of America Patent
Stats
-
Mar 20, 2018
Issued Date -
N/A
app pub date -
Sep 1, 2017
filing date -
Sep 2, 2016
priority date (Note) -
In Force
status (Latency Note)
Importance
Abstract
Systems and methods for providing convolutional neural network based image synthesis using localized loss functions is disclosed. A first image including desired content and a second image including a desired style are received. The images are analyzed to determine a local loss function. The first and second images are merged using the local loss function to generate an image that includes the desired content presented in the desired style. Similar processes can also be utilized to generate image hybrids and to perform on-model texture synthesis. In a number of embodiments, Condensed Feature Extraction Networks are also generated using a convolutional neural network previously trained to perform image classification, where the Condensed Feature Extraction Networks approximates intermediate neural activations of the convolutional neural network utilized during training.
First Claim
Family
International Classification(s)
- [Classification Symbol]
- [Patents Count]
Cited Art Landscape
Patent Citation Ranking
Recipient Email Address
Recipient Email Address
Comment
Recipient Email Address
Add to Portfolio(s)
To add this patent to one, or more, of your portfolios, simply click the add button.
This Patent is in these Portfolios:
Add to additional portfolios:
Last Refreshed On:
Changes done successfully