APPARATUS AND METHOD OF GUIDED NEURAL NETWORK MODEL FOR IMAGE PROCESSING

Smart overview of the Invention

An innovative apparatus and method for image processing is introduced, utilizing a guided neural network model. The system comprises three main components: a guidance map generator, a synthesis network, and an accelerator. The guidance map generator takes two images—a content image and a style image—and produces multiple guidance maps from each. These maps serve as critical inputs for the synthesis network, which combines them to extract guidance information essential for the final output.

Functionality of Components

The guidance map generator plays a pivotal role by generating guidance maps that capture distinct features from both the content and style images. The synthesis network then processes these maps to synthesize guidance information. Finally, the accelerator applies this information to create an output image that reflects the style of the second image while retaining the content of the first. This approach enhances the ability to stylize images effectively.

Background Context

Traditional graphics processing techniques have evolved from fixed-function computational units to more programmable systems, allowing for diverse operations on graphics data. While deep neural networks (DNNs) have simplified image processing tasks, they often lack sufficient guidance mechanisms, which are crucial for achieving high-quality results in applications like gaming and animation.

Technical Architecture

The architecture involves a graphics processing unit (GPU) that connects with processor cores to expedite various operations. This setup allows for efficient command processing through dedicated circuitry designed specifically for graphics and machine-learning tasks. The system can handle complex operations like style transfer, where the goal is to merge the stylistic elements of one image with the content of another.

Potential Applications

• Non-photorealistic rendering in gaming and animation.
• Photorealistic portrait rendering for film production.
• General-purpose GPU functions for various graphical applications.
• Enhanced user accessibility in image processing tasks.