High-Resolution Tiled Clothes Generation from a Model
Source abstract
Abstract
Many image translation methods based on conditional generative adversarial networks can transform images from one domain to another, but the results of many methods are at a low resolution. We present a modified pix2pixHD model, which generates high-resolution tiled clothing from a model wearing clothes. We choose a single Markovian discriminator instead of a multi-scale discriminator for a faster training speed, added a perceptual loss term, and improved the feature matching loss. Deeper feature maps have lower weights when calculating losses. A dataset was specifically built for this improved model, which contains over 20,000 paired high-quality tiled clothing. The experimental results demonstrate the feasibility of our improved method and can be extended to other fields.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Generative Adversarial Networks and Image Synthesis · Advanced Image Processing Techniques · Advanced Vision and Imaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Donghua University
References (32)
Show source-provided references
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