Interactive Latent Interpolation on MNIST Dataset
This work provides an incremental improvement for web/mobile applications needing fast GAN-based image generation and interpolation.
The paper tackles interactive latent interpolation for MNIST images using a web-based GAN with dimensionality reduction, achieving generation speeds of 0.2 milliseconds in browsers to enable real-time animations.
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.