@inproceedings{08720456459846b1af468e50c6549f21,
title = "CLIPascene: Scene Sketching with Different Types and Levels of Abstraction",
abstract = "In this paper, we present a method for converting a given scene image into a sketch using different types and multiple levels of abstraction. We distinguish between two types of abstraction. The first considers the fidelity of the sketch, varying its representation from a more precise portrayal of the input to a looser depiction. The second is defined by the visual simplicity of the sketch, moving from a detailed depiction to a sparse sketch. Using an explicit disentanglement into two abstraction axes - and multiple levels for each one - provides users additional control over selecting the desired sketch based on their personal goals and preferences. To form a sketch at a given level of fidelity and simplification, we train two MLP networks. The first network learns the desired placement of strokes, while the second network learns to gradually remove strokes from the sketch without harming its recognizability and semantics. Our approach is able to generate sketches of complex scenes including those with complex backgrounds (e.g. natural and urban settings) and subjects (e.g. animals and people) while depicting gradual abstractions of the input scene in terms of fidelity and simplicity. https://clipascene.github.io/CLIPascene/",
author = "Yael Vinker and Yuval Alaluf and Daniel Cohen-Or and Ariel Shamir",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023 ; Conference date: 02-10-2023 Through 06-10-2023",
year = "2023",
doi = "https://doi.org/10.1109/ICCV51070.2023.00383",
language = "الإنجليزيّة",
series = "Proceedings of the IEEE International Conference on Computer Vision",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4123--4133",
booktitle = "Proceedings - 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023",
address = "الولايات المتّحدة",
}