CoSketcher: Collaborative and Iterative Sketch Generation with LLMs under Linguistic and Spatial Control

Abstract
Sketching serves as both a medium for visualizing ideas and a process for creative iteration. While early neural sketch generation methods rely on category-specific data and lack generalization and iteration capability, recent advances in Large Language Models (LLMs) have opened new possibilities for more flexible and semantically guided sketching. In this work, we present CoSketcher, a controllable and iterative sketch generation system that leverages the prior knowledge and textual reasoning abilities of LLMs to align with the creative iteration process of human sketching. CoSketcher introduces a novel XML-style sketch language that represents stroke-level information in structured format, enabling the LLM to plan and generate complex sketches under both linguistic and spatial control. The system supports visual appealing sketch construction, including skeleton-contour decomposition for volumetric shapes and layout-aware reasoning for object relationships. Through extensive evaluation, we demonstrate that our method generates expressive sketches across both in-distribution and out-of-distribution categories, while also supporting scene-level composition and controllable iteration. Our method establishes a new paradigm for controllable sketch generation using off-the-shelf LLMs, with broad implications for creative human-AI collaboration.
Description

CCS Concepts: Human-centered computing → Human computer interaction (HCI)

        
@inproceedings{
10.2312:pg.20251298
, booktitle = {
Pacific Graphics Conference Papers, Posters, and Demos
}, editor = {
Christie, Marc
and
Han, Ping-Hsuan
and
Lin, Shih-Syun
and
Pietroni, Nico
and
Schneider, Teseo
and
Tsai, Hsin-Ruey
and
Wang, Yu-Shuen
and
Zhang, Eugene
}, title = {{
CoSketcher: Collaborative and Iterative Sketch Generation with LLMs under Linguistic and Spatial Control
}}, author = {
Mei, Liwen
and
Guan, Manhao
and
Zheng, Yifan
and
Zhang, Dongliang
}, year = {
2025
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-03868-295-0
}, DOI = {
10.2312/pg.20251298
} }
Citation