CustomSketching: Sketch Concept Extraction for Sketch-based Image Synthesis and Editing
Chufeng Xiao, Hongbo Fu

TL;DR
CustomSketching introduces a novel framework for extracting sketch concepts from image-sketch pairs, enabling fine-grained, sketch-based image synthesis and editing, thus providing more control than traditional text-based personalization methods.
Contribution
The paper proposes a dual-sketch representation and a two-stage framework for effective sketch concept extraction, enhancing control over image synthesis and editing.
Findings
Outperforms adapted baselines in experiments
Effective in fine-grained image editing
User study confirms superiority
Abstract
Personalization techniques for large text-to-image (T2I) models allow users to incorporate new concepts from reference images. However, existing methods primarily rely on textual descriptions, leading to limited control over customized images and failing to support fine-grained and local editing (e.g., shape, pose, and details). In this paper, we identify sketches as an intuitive and versatile representation that can facilitate such control, e.g., contour lines capturing shape information and flow lines representing texture. This motivates us to explore a novel task of sketch concept extraction: given one or more sketch-image pairs, we aim to extract a special sketch concept that bridges the correspondence between the images and sketches, thus enabling sketch-based image synthesis and editing at a fine-grained level. To accomplish this, we introduce CustomSketching, a two-stage…
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Taxonomy
TopicsHandwritten Text Recognition Techniques · Human Motion and Animation · Computer Graphics and Visualization Techniques
