Int-Papercut: An Intelligent Pattern Generation with Papercut Style Based on Convolutional Neural Network

Paper cutting is a traditional folk art, as a world intangible cultural heritage (ICH), it expresses people's social life and folk activities. However, papercut production still relies on rich pattern creation experience and fixed pattern, which limits the creation of paper-cut art, especially for novices. To address this gap, we put forward Int-Papercut, a new papercut pattern generation system based on convolutional Neural Network (CNN), which can recognize and mark the patterns of the input photos, and use the basic symbols of papercut to match and fill in, and finally convert the photos into clip-cut style patterns. Empirical qualitative data from two papercut experts and 8 papercut novices show Int-Papercut facilitated their understanding of paper cutting and production. Our system is expected to support users to freely create papercut works with their favorite pictures, and promote the protection, development and application of papercut culture.