SketchyCOCO: Image Generation From Freehand Scene Sketches

Chengying Gao, Qi Liu, Qi Xu, Limin Wang, Jianzhuang Liu, Changqing Zou; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 5174-5183

Abstract


We introduce the first method for automatic image generation from scene-level freehand sketches. Our model allows for controllable image generation by specifying the synthesis goal via freehand sketches. The key contribution is an attribute vector bridged Generative Adversarial Network called EdgeGAN, which supports high visual-quality object-level image content generation without using freehand sketches as training data. We have built a large-scale composite dataset called SketchyCOCO to support and evaluate the solution. We validate our approach on the tasks of both object-level and scene-level image generation on SketchyCOCO. Through quantitative, qualitative results, human evaluation and ablation studies, we demonstrate the method's capacity to generate realistic complex scene-level images from various freehand sketches.

Related Material


[pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Gao_2020_CVPR,
author = {Gao, Chengying and Liu, Qi and Xu, Qi and Wang, Limin and Liu, Jianzhuang and Zou, Changqing},
title = {SketchyCOCO: Image Generation From Freehand Scene Sketches},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}