Summary of Content-conditioned Generation Of Stylized Free Hand Sketches, by Jiajun Liu et al.
Content-Conditioned Generation of Stylized Free hand Sketches
by Jiajun Liu, Siyuan Wang, Guangming Zhu, Liang Zhang, Ning Li, Eryang Gao
First submitted to arxiv on: 9 Jan 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed adversarial generative network can accurately generate realistic free-hand sketches with various styles, overcoming limitations in related fields such as military applications. The model uses a novel approach to disentangle painters’ styles from known free-hand sketches, enabling the generation of images with specific styles. Furthermore, it demonstrates impressive visual quality, content accuracy, and style imitation on SketchIME. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers created a special computer program that can make realistic drawings by hand, but in different styles. This is useful for fields like military, where lots of pictures are needed, but it’s hard to get people to draw them all. The program uses a new way to mix and match different drawing styles to create new ones. It also works well on a test set that wasn’t part of the training data. |
