Work

Hyperstroke: A Novel High-quality Stroke Representation for Assistive Artistic Drawing

Year: 2024

Type: conference-paper

Abstract: Assistive drawing aims to facilitate the creative process by providing intelligent guidance to artists.Existing solutions often fail to effectively model intricate stroke details or adequately address the temporal aspects of drawing.We introduce hyperstroke, a novel stroke representation designed to capture precise fine stroke details, including RGB appearance and alpha-channel opacity.Using a Vector Quantization approach, hyperstroke learns compact tokenized representations of strokes from real-life drawing videos of artistic drawing.With hyperstroke, we propose to model assistive drawing via a transformer-based architecture, to enable intuitive and user-friendly drawing applications, which are experimented in our exploratory evaluation.

Source: SIGGRAPH Asia Technical Communications

DOI: 10.1145/3681758.3697985

Authors: Haoyun Qin, Jian Lin, Hanyuan Liu, Xueting Liu, Chengze Li

Institutions: University of Pennsylvania, Saint Francis University, City University of Hong Kong

Language: English

Topic: Generative Adversarial Networks and Image Synthesis

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Research Grants Council, University Grants Committee

Award: G346266166