Animal Face Image Generation With Pretrained Style Transfer
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Solution Overview
Problem
Conventional video interactive applications lack the ability to transform images into diverse styles, resulting in a limited user experience and failing to meet personalized user requirements for image style transformation.
Innovation Solution
A method and apparatus for generating animal face style images using a pre-trained animal face style image generation model, trained with human and animal face sample images, to transform human faces into animal faces, enhancing image editing functions and user experience in video interactive applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional video interactive applications use limited style transformation capabilities, then the system complexity remains low, but the user experience and adaptability deteriorate due to insufficient personalization options
Solution Approach 1:
The patent segments the image style transformation process into two distinct models: (1) an animal face generation model that transforms human faces into animal faces, and (2) an animal face style image generation model that applies style transfer. This segmentation allows each model to specialize in a specific task, improving overall adaptability while managing complexity through modular architecture.
Solution Approach 2:
The patent implements preliminary action by pre-training both the animal face generation model and the style image generation model before deployment. The models are trained offline using extensive datasets of human faces and animal face images, so that when deployed in video interactive applications, they can perform real-time style transformation without requiring complex runtime processing.
2Adaptability or versatility
If the system implements personalized image style transformation, then user experience improves, but the loss of time increases due to extensive model training requirements
Solution Approach 1:
The patent applies preliminary action by performing all model training operations offline before the application is deployed to users. The animal face generation model and style image generation model are trained in advance using large datasets, so that during actual use in video interactive applications, the models can quickly generate personalized animal face style images without requiring users to wait for training processes.
Solution Approach 2:
The patent uses copying by training models on extensive datasets of animal face images and human face images. The models learn to generate realistic animal face styles by copying patterns and features from the training data, enabling personalized style transformation without requiring real-time access to extensive image libraries during application execution.
Data Source
AI summary
An animal face style image generation method, a model training method, and a device are provided. The method includes: acquiring an original human face image; and obtaining an animal face style image corresponding to the original human face image. The animal face style image refers to an image obtained by transforming a human face on the original human face image into an animal face, the animal face style image generation model is obtained by training with a first human face sample image and a first animal face style sample image, the first animal face style sample image is generated from the first human face sample image by a pre-trained animal face generation model, and the animal face generation model is obtained by training with a second human face sample image and a first animal face sample image.