Version 1
: Received: 19 October 2023 / Approved: 19 October 2023 / Online: 19 October 2023 (16:44:14 CEST)
How to cite:
Kim, B.; Yang, H.; Min, K. TOLGAN: An End-to-end framework for producing Traditional Orient Landscape. Preprints2023, 2023101290. https://doi.org/10.20944/preprints202310.1290.v1
Kim, B.; Yang, H.; Min, K. TOLGAN: An End-to-end framework for producing Traditional Orient Landscape. Preprints 2023, 2023101290. https://doi.org/10.20944/preprints202310.1290.v1
Kim, B.; Yang, H.; Min, K. TOLGAN: An End-to-end framework for producing Traditional Orient Landscape. Preprints2023, 2023101290. https://doi.org/10.20944/preprints202310.1290.v1
APA Style
Kim, B., Yang, H., & Min, K. (2023). TOLGAN: An End-to-end framework for producing Traditional Orient Landscape. Preprints. https://doi.org/10.20944/preprints202310.1290.v1
Chicago/Turabian Style
Kim, B., Heekyung Yang and Kyungha Min. 2023 "TOLGAN: An End-to-end framework for producing Traditional Orient Landscape" Preprints. https://doi.org/10.20944/preprints202310.1290.v1
Abstract
We present TOLGAN that generates traditional oriental landscape (TOL) image from a map that specifies the locations and shapes of the elements composing TOL. Users can create a TOL map by using a user interface or a segmentation scheme from a photograph. We design the generator of TOLGAN as a series of decoding layers where the map is applied between the layers. The generated TOL image is further enhanced through an AdaIN architecture. The discriminator of TOLGAN processes a generated image and its groundtruth TOL artwork image. TOLGAN is trained through a dataset composed of paired TOL artwork images and their TOL maps. We present a tool through which users can produce a TOL map by specifying and organizing the elements of TOL artworks. TOLGAN successfully generates a series of TOL images from the TOL map. We evaluate our approach using a quantitative way by estimating FID and ArtFID scores and a qualitative way by executing two user studies. Through these studies, we prove the excellence of our approach by comparing our results with those from several important existing works.
Keywords
traditional oriental landscape (TOL); GAN; SPADE; generator; discriminator
Subject
Computer Science and Mathematics, Computer Vision and Graphics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
