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D3.2 – Framework of Adaptive style generation based on Autoencoder Networks

D3.2 – Framework of Adaptive style generation based on Autoencoder Networks

  • Posted by Eleonora Bongiovanni
  • On March 28, 2022
  • 0 Comments
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  • Last Updated May 26, 2022

D3.2 - Framework of Adaptive style generation based on Autoencoder Networks

CONFIDENTIAL DELIVERABLE, for more information contact us contact@inedit-project.eu

 

Authors: AIMEN

 

Abstract: D3.2 aims to present the developed software modules to the partners of the consortium, explaining  the methodology, algorithms and data used for the development, as well as the interfaces that are provided for the integration with other softwares.

The work carried on has been structured in three software modules that interact between
themselves and with the other modules of WP3:

  • Generative module: This module can generate 3D models of random pieces of furniture. The
    inputs of the module are the type of furniture and a random seed that determines the style.
  • Recommendation module: This module can recommend existing pieces of furniture, given
    other pieces or some keywords about the generation.
  • Community feedback module: This module is able to link the community interactions
    (recommendations and/or community feedback) with the generation module, to create
    furniture that matches certain trends or styles, and acting as a guide of the generative
    module.
 

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