Image Processing Model for Authentic Facial Beautification

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Solution Overview

Problem

Existing facial image beautification technologies often result in poor authenticity and insufficient beautification effects due to imprecise special effect application, leading to a fake appearance and inadequate user experience.

Innovation Solution

An image processing method and apparatus that uses a generative adversarial network to remove conflicting objects from facial images and superimpose adjustable target objects, ensuring the special effect object is accurately applied, thereby enhancing the authenticity and beautification of the image.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If special effect data is extracted from a database and applied to facial image locations, then the special effect can be applied, but the authenticity and naturalness of the beautification effect deteriorates due to conflicting objects interfering with the special effect object

Engineering Contradiction:

Improveauthenticity of special effectVSAvoidconflicting object interference

Core Design Contradiction:

ReliabilityVSObject-generated harmful factors

Solution Approach 1:

The patent extracts and removes conflicting objects from the facial image before applying the special effect. The generator network specifically identifies and eliminates interfering elements (such as skin texture, pores, or other facial features) that would compromise the authenticity of the special effect object, thereby resolving the contradiction between applying special effects and maintaining image authenticity.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent performs preliminary removal of conflicting objects before the special effect application. By pre-processing the image to eliminate interfering elements and then superimposing the special effect object onto the cleaned image, the system ensures that the special effect appears authentic without interference from conflicting visual elements.

Inventive Principle:

Principle #10Preliminary action

2Ease of manufacture

If traditional special effect application methods are used, then the process is simple, but the beautification effect is insufficient due to imprecise application and fake appearance

Engineering Contradiction:

Improvesimplicity of processingVSAvoidprecision of special effect application

Core Design Contradiction:

Ease of manufactureVSManufacturing precision

Solution Approach 1:

The patent introduces a generator network as an intermediary component between the original image and the final special effect output. This intermediary automatically learns and applies the precise mapping between image regions and special effect placements, eliminating the need for manual annotation while achieving high precision in special effect application and natural integration.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces manual or rule-based special effect application mechanisms with a deep learning-based generator network. This substitution enables automatic, precise, and context-aware special effect placement that adapts to different facial features and images, significantly improving precision while maintaining ease of use through automated processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If conflicting objects are not removed, then the processing is faster, but the user experience deteriorates due to poor authenticity and inadequate beautification

Engineering Contradiction:

Improveprocessing speedVSAvoiduser experience

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The patent merges multiple functions into a single integrated generator network: conflicting object removal, special effect object generation, and precise positioning are all performed simultaneously by one model. This consolidation maintains processing speed while delivering superior user experience through authentic and natural-looking beautification effects that automatically adapt to different input images.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS20240273794A1Image processing method, training method for an image processing model, electronic device, and medium

Publication Date: 2024.08.15 BEIJING ZITIAO NETWORK TECH CO LTD

AI summary

Embodiments of the present disclosure disclose an image processing method, a training method for an image processing model, an electronic device and a medium. The image processing method comprises: inputting an image to be processed into an image processing model in response to a special effect trigger instruction; and outputting a target image from the image processing model, wherein the target image comprises a special effect object and a conflicting object corresponding to the special effect object is removed in the target image, wherein the image processing model is trained based on an image with the conflicting object removed and a target object superimposed, wherein the target object comprises an adjustable object having a same presentation effect as the special effect object, and the image with the conflicting object removed is generated by a generator trained based on a generative adversarial network.