Interactive Latent Interpolation on MNIST Dataset

TL;DR

This paper explores web-based GANs with dimensionality reduction for fast image synthesis, interpolation, and animation, demonstrating rapid generation and a modern UI for interactive visualizations.

Contribution

It introduces a web-based GAN architecture leveraging dimensionality reduction for real-time image synthesis and interpolation, with a novel UI for interactive animations.

Findings

Generation speed of 0.2 milliseconds in browser

Successful visual interpolation between images

Creation of interactive animations on web and mobile

Abstract

This paper will discuss the potential of dimensionality reduction with a web-based use of GANs. Throughout a variety of experiments, we show synthesizing visually-appealing samples, interpolating meaningfully between samples, and performing linear arithmetic with latent vectors. GANs have proved to be a remarkable technique to produce computer-generated images, very similar to an original image. This is primarily useful when coupled with dimensionality reduction as an effective application of our algorithm. We proposed a new architecture for GANs, which ended up not working for mathematical reasons later explained. We then proposed a new web-based GAN that still takes advantage of dimensionality reduction to speed generation in the browser to .2 milliseconds. Lastly, we made a modern UI with linear interpolation to present the work. With the speedy generation, we can generate so fast that we can create an animation type effect that we have never seen before that works on both web and mobile.