素描
计算机科学
对象(语法)
生成语法
生成模型
帧(网络)
序列(生物学)
草图识别
人工智能
计算机图形学(图像)
计算机视觉
算法
手势
生物
手势识别
电信
遗传学
作者
Ting Lu,Wangchenhui Wu,Qiang Wang,Haoge Deng,Di Kong,Yonggang Qi
标识
DOI:10.1109/ic-nidc59918.2023.10390879
摘要
We present SketchCreator, a text-to-sketch generative frame-work built on diffusion models, which can produce human sketches given a text description. Specifically, sketches are represented in a sequence of stroke points, where our model aims to directly learn the distribution of these ordered points under the guidance of the prompt, i.e., text description. Uniquely, different from prior arts focusing on single-object sketch generation, our model can flexibly generate both the single sketch object and scene sketches conditioned on the prompt. Particularly, our model can generate the scene sketch uniformly without explicitly determining the layout of the scene, which is typically required by previous works. Consequently, the produced objects in a scene sketch are more reasonably organized and visually appealing. Additionally, our model can be readily applied to text-conditioned sketch editing which is of great practical usage. Experimental results on QuickDraw and FS-COCO validate the effectiveness of our model.
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