Compositional Neural Textures

arXiv:2404.12509v1 Announce Type: cross
Abstract: Texture plays a vital role in enhancing visual richness in both real photographs and computer-generated imagery. However, the process of editing textures often involves laborious and repetitive manual adjustments of textons, which are the small, recurring local patterns that define textures. In this work, we introduce a fully unsupervised approach for representing textures using a compositional neural model that captures individual textons. We represent each texton as a 2D Gaussian function whose spatial support approximates …

abstract arxiv computer computer-generated cs.ai cs.cv cs.gr cs.lg editing generated however patterns photographs process role small texture type unsupervised visual vital work