2 research outputs found
Nested Scale Editing for Conditional Image Synthesis
We propose an image synthesis approach that provides stratified navigation in
the latent code space. With a tiny amount of partial or very low-resolution
image, our approach can consistently out-perform state-of-the-art counterparts
in terms of generating the closest sampled image to the ground truth. We
achieve this through scale-independent editing while expanding scale-specific
diversity. Scale-independence is achieved with a nested scale disentanglement
loss. Scale-specific diversity is created by incorporating a progressive
diversification constraint. We introduce semantic persistency across the scales
by sharing common latent codes. Together they provide better control of the
image synthesis process. We evaluate the effectiveness of our proposed approach
through various tasks, including image outpainting, image superresolution, and
cross-domain image translation
Image-to-Image Translation: Methods and Applications
Image-to-image translation (I2I) aims to transfer images from a source domain
to a target domain while preserving the content representations. I2I has drawn
increasing attention and made tremendous progress in recent years because of
its wide range of applications in many computer vision and image processing
problems, such as image synthesis, segmentation, style transfer, restoration,
and pose estimation. In this paper, we provide an overview of the I2I works
developed in recent years. We will analyze the key techniques of the existing
I2I works and clarify the main progress the community has made. Additionally,
we will elaborate on the effect of I2I on the research and industry community
and point out remaining challenges in related fields.Comment: 24 pages, 21 figure