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Image synthesis Technology at High Resolution
The task of image-based virtual try-on aims to transfer a target clothing item onto the corresponding region of a person, which is commonly tackled by fitting the item to the desired body part and fusing the warped item with the person. While an increasing number of studies have been conducted, the resolution of synthesized images is still limited to low (e.g., 256x192), which acts as the critical limitation against satisfying online consumers. We argue that the limitation stems from several challenges: as the resolution increases, the artifacts in the misaligned areas between the warped clothes and the desired clothing regions become
noticeable in the final results; the architectures used in existing methods have low performance in generating highquality body parts and maintaining the texture sharpness of the clothes. To address the challenges, we propose a novel virtual try-on method called VITON-HD that successfully synthesizes 1024x768 virtual try-on images.


Super Resolution Technology
There are many mechanisms for creating AI art, including procedural 'rule-based' generation of images using mathematical patterns, algorithms which simulate brush strokes and other painted effects, and artificial intelligence or deep learning algorithms such as generative adversarial networks and transformers.
Since their design in 2014, generative adversarial networks (GANs) are often used by AI artists. This system uses a "generator" to create new images and a "discriminator" to decide which created images are considered successful. More recent models use Vector Quantized Generative Adversarial Network and Contrastive Language–Image Pre-training (VQGAN+CLIP).
DeepDream, released by Google in 2015, uses a convolutional neural network to find and enhance patterns in images via algorithmic pareidolia, thus creating a dream-like psychedelic appearance in the deliberately over-processed images.
Several programs made by large companies use AI to generate a variety of images based on various text prompts. They include OpenAI's DALL-E which released a series of images in January 2021, Google Brain's Imagen and Parti which was announced in May 2022 and Microsofts' NUWA-Infinity.
There are many other AI art generation programs, ranging in complexity from simple consumer-facing mobile apps to Jupyter notebooks that require powerful GPUs to run effectively.
Based on the characteristics and algorithms of various models of stylegan, we apply the learning method optimized for artwork and provide it to the service. In particular, it uses super resolution technology to create clear and high-quality images.