Can Giraffes Become Birds? An Evaluation of Image-to-image Translation for Data Generation

by   Daniel V. Ruiz, et al.

There is an increasing interest in image-to-image translation with applications ranging from generating maps from satellite images to creating entire clothes' images from only contours. In the present work, we investigate image-to-image translation using Generative Adversarial Networks (GANs) for generating new data, taking as a case study the morphing of giraffes images into bird images. Morphing a giraffe into a bird is a challenging task, as they have different scales, textures, and morphology. An unsupervised cross-domain translator entitled InstaGAN was trained on giraffes and birds, along with their respective masks, to learn translation between both domains. A dataset of synthetic bird images was generated using translation from originally giraffe images while preserving the original spatial arrangement and background. It is important to stress that the generated birds do not exist, being only the result of a latent representation learned by InstaGAN. Two subsets of common literature datasets were used for training the GAN and generating the translated images: COCO and Caltech-UCSD Birds 200-2011. To evaluate the realness and quality of the generated images and masks, qualitative and quantitative analyses were made. For the quantitative analysis, a pre-trained Mask R-CNN was used for the detection and segmentation of birds on Pascal VOC, Caltech-UCSD Birds 200-2011, and our new dataset entitled FakeSet. The generated dataset achieved detection and segmentation results close to the real datasets, suggesting that the generated images are realistic enough to be detected and segmented by a state-of-the-art deep neural network.


page 1

page 3

page 4

page 6


Generative Adversarial Network Applications in Creating a Meta-Universe

Generative Adversarial Networks (GANs) are machine learning methods that...

LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images

The intelligent perception of endoscopic vision is appealing in many com...

A comparative evaluation of image-to-image translation methods for stain transfer in histopathology

Image-to-image translation (I2I) methods allow the generation of artific...

DEPAS: De-novo Pathology Semantic Masks using a Generative Model

The integration of artificial intelligence into digital pathology has th...

Towards Adversarial Retinal Image Synthesis

Synthesizing images of the eye fundus is a challenging task that has bee...

Inner Space Preserving Generative Pose Machine

Image-based generative methods, such as generative adversarial networks ...

Seamless Satellite-image Synthesis

We introduce Seamless Satellite-image Synthesis (SSS), a novel neural ar...

Please sign up or login with your details

Forgot password? Click here to reset