He, Yu; Jin, Yi-Han; Liu, Ying-Tian; Lu, Bao-Li; Yu, Ge Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v 14250 LNCS, p 200-214, 2024, Computer-Aided Design and Computer Graphics - 18th International Conference, CAD/Graphics 2023, Proceedings;

Abstract:

We introduce an automated pipeline for synthesizing texture maps in complex indoor scenes. With a style sample or color palette as inputs, our pipeline predicts theme color for each room using a GAN-based method, before generating texture maps using combinatorial optimization. We consider constraints on material selection, color correlation, and color palette matching. Our experiments show the pipeline’s ability to produce pleasing and harmonious textures for diverse layouts and our contribution of an interior furniture texture dataset with 4,337 texture images.

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. (31 refs.)