Tiled Diffusion

TL;DR

Tiled Diffusion is a novel diffusion-based method that automates the creation of seamless, interconnected image tiles across diverse domains, enhancing scalability and flexibility in digital art and texture synthesis.

Contribution

It extends diffusion models to support automatic, cohesive tiling of multiple images, addressing limitations of previous texture-focused approaches.

Findings

Supports a wide range of tiling scenarios

Enables seamless integration of multiple images

Automates the tiling process without manual intervention

Abstract

Image tiling -- the seamless connection of disparate images to create a coherent visual field -- is crucial for applications such as texture creation, video game asset development, and digital art. Traditionally, tiles have been constructed manually, a method that poses significant limitations in scalability and flexibility. Recent research has attempted to automate this process using generative models. However, current approaches primarily focus on tiling textures and manipulating models for single-image generation, without inherently supporting the creation of multiple interconnected tiles across diverse domains. This paper presents Tiled Diffusion, a novel approach that extends the capabilities of diffusion models to accommodate the generation of cohesive tiling patterns across various domains of image synthesis that require tiling. Our method supports a wide range of tiling scenarios, from self-tiling to complex many-to-many connections, enabling seamless integration of multiple images. Tiled Diffusion automates the tiling process, eliminating the need for manual intervention and enhancing creative possibilities in various applications, such as seamlessly tiling of existing images, tiled texture creation, and 360$^\circ$ synthesis.