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Sketch completion and recognition method and device based on generative adversarial network

A sketch recognition and generative technology, applied in the field of computer vision, can solve the problem of incomplete sketch recognition that has not been paid attention and solved, and no clear mapping relationship, etc. Effect

Active Publication Date: 2019-08-20
INST OF SOFTWARE - CHINESE ACAD OF SCI
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  • Description
  • Claims
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AI Technical Summary

Benefits of technology

This patented technology describes various methods called conditional Explanations Trellis Anomaly Currents (CXAC) Controlled GAN or Deep Belief Neural Network (DBNN)-based techniques such as convolutional neural networks (CNT's) and generalized incrementality transfer operators (GATMs)). These technical improvements aim to make better understanding of complex images more accessible than previously possible due to their repetitive nature.

Problems solved by technology

This technical problem addressed by this patents relates to improving sketch understanding capabilities during sketched media analysis processes due to imperfections like partial sketchings caused by poorly understood sketches or even partially hidden areas called background clothing. Current methods involve generating detailed sketches manually without sufficient consideration, leading to errors when analyzing them. Therefore, advanced mathematical models capable of predictive processing of these types of drawbacks would provide more accurate solutions than previous approaches.

Method used

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  • Sketch completion and recognition method and device based on generative adversarial network
  • Sketch completion and recognition method and device based on generative adversarial network
  • Sketch completion and recognition method and device based on generative adversarial network

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Abstract

The invention discloses a sketch completion and recognition method and device based on a generative adversarial network. The sketch completion and recognition method comprises the following steps: (1)based on a conditional generative adversarial neural network, improving the generative adversarial neural network by utilizing a cascading strategy according to the characteristic that a sketch is sparse relative to semantic information of a color picture; (2) expanding the category universality of the sketch completion network, setting a sketch recognition task as an auxiliary task, and adding asketch recognition auxiliary network in the network structure; (3) applying the sketch completion method to the recognition task of the incomplete sketch, the image retrieval task based on the incomplete sketch and the sketch scene editing task; and (6) integrating the sketch completion method to form a sketch completion application platform, supporting application functions of interactive sketchcompletion, sketch completion and identification, sketch scene segmentation and completion, interactive sketch completion assistance and the like, and being capable of being applied to various devices and terminals such as a PC, a mobile phone, a tablet personal computer and an electronic whiteboard.

Description

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Claims

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Application Information

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Owner INST OF SOFTWARE - CHINESE ACAD OF SCI
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