✳flâneur — a map of the web's best reading

A Very Short Introduction to Inception Score(IS) | by Kailash Ahirwar | Medium

kailashahirwar.medium.com · 735 words · saved by 1 readers

Generative Adversarial Networks or GANs for short were successful in generating high-quality images, videos, and audio. We have seen various use cases of GANs. Some of the popular GAN networks are BigGAN, StyleGAN, GameGAN, and PGGAN. They have widespread adoption in the industry and academia. But, evaluation of generated samples can be very tricky and prone to errors if done subjectively by humans. IS was introduced to overcome this problem. The Inception Score(IS) is an objective performance metric, used to evaluate the quality of generated images or synthetic images, generated by Generative Adversarial Networks(GANs). It measures how realistic and diverse the output images are. It can be used instead of subjective evaluation by humans. After FID(Frechlet Inception Distance), it is the second most important evaluation performance metric. I have written an article explaining FID and how to calculate it. It was introduced in 2016 by Tim Salimans et al., in the paper titled “Improved Te

Machine Learning Artificial Intelligence Deep Learning Computer Vision A Very Short Introduction to Inception Score(IS) Kailash Ahirwar 4 min read · Feb 24, 2021 -- Listen Share Generative Adversarial Networks or GANs for short were successful in generating high-quality images, videos, and audio. We have seen various use cases of GANs. Some of the popular GAN networks are BigGAN, StyleGAN, GameGAN, and PGGAN. They have widespread adoption in the industry and academia. But, evaluation of generated samples can be very tricky and prone to errors if done subjectively by humans. IS was introduced t

Explore this link on the map →

related reading