Paper ID: 2312.03993

Style Transfer to Calvin and Hobbes comics using Stable Diffusion

Sloke Shrestha, Sundar Sripada V. S., Asvin Venkataramanan

This project report summarizes our journey to perform stable diffusion fine-tuning on a dataset containing Calvin and Hobbes comics. The purpose is to convert any given input image into the comic style of Calvin and Hobbes, essentially performing style transfer. We train stable-diffusion-v1.5 using Low Rank Adaptation (LoRA) to efficiently speed up the fine-tuning process. The diffusion itself is handled by a Variational Autoencoder (VAE), which is a U-net. Our results were visually appealing for the amount of training time and the quality of input data that went into training.

Submitted: Dec 7, 2023