Tileable Texture

Tileable texture generation focuses on creating images that seamlessly repeat without noticeable artifacts, crucial for applications like material design and virtual environments. Recent research emphasizes methods leveraging deep learning, particularly generative adversarial networks (GANs) and diffusion models, to synthesize diverse and high-quality tileable textures, often guided by text prompts or semantic segmentation maps. Researchers are also developing novel metrics to objectively evaluate tileability and exploring implicit neural representations for efficient high-resolution texture generation. These advancements improve the control and quality of generated textures, impacting fields ranging from computer graphics to material science.