Domain Agnostic Image-to-image Translation using Low-Resolution Conditioning

by   Mohamed Abid, et al.

Generally, image-to-image translation (i2i) methods aim at learning mappings across domains with the assumption that the images used for translation share content (e.g., pose) but have their own domain-specific information (a.k.a. style). Conditioned on a target image, such methods extract the target style and combine it with the source image content, keeping coherence between the domains. In our proposal, we depart from this traditional view and instead consider the scenario where the target domain is represented by a very low-resolution (LR) image, proposing a domain-agnostic i2i method for fine-grained problems, where the domains are related. More specifically, our domain-agnostic approach aims at generating an image that combines visual features from the source image with low-frequency information (e.g. pose, color) of the LR target image. To do so, we present a novel approach that relies on training the generative model to produce images that both share distinctive information of the associated source image and correctly match the LR target image when downscaled. We validate our method on the CelebA-HQ and AFHQ datasets by demonstrating improvements in terms of visual quality. Qualitative and quantitative results show that when dealing with intra-domain image translation, our method generates realistic samples compared to state-of-the-art methods such as StarGAN v2. Ablation studies also reveal that our method is robust to changes in color, it can be applied to out-of-distribution images, and it allows for manual control over the final results.


page 7

page 8

page 9

page 14

page 15

page 16

page 17

page 18


Image-to-Image Translation with Low Resolution Conditioning

Most image-to-image translation methods focus on learning mappings acros...

Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound

Unsupervised image-to-image translation is a class of computer vision pr...

ACE: Zero-Shot Image to Image Translation via Pretrained Auto-Contrastive-Encoder

Image-to-image translation is a fundamental task in computer vision. It ...

Unpaired Image-to-Image Translation via Latent Energy Transport

Image-to-image translation aims to preserve source contents while transl...

Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network

Image-to-Image (I2I) translation is a heated topic in academia, and it a...

EDIT: Exemplar-Domain Aware Image-to-Image Translation

Image-to-image translation is to convert an image of the certain style t...

DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation

We present the DeepHist - a novel Deep Learning framework for augmenting...

Please sign up or login with your details

Forgot password? Click here to reset