Summary of Visioblend: Sketch and Stroke-guided Denoising Diffusion Probabilistic Model For Realistic Image Generation, by Harshkumar Devmurari et al.
VisioBlend: Sketch and Stroke-Guided Denoising Diffusion Probabilistic Model for Realistic Image Generation
by Harshkumar Devmurari, Gautham Kuckian, Prajjwal Vishwakarma, Krunali Vartak
First submitted to arxiv on: 15 May 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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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 This paper proposes VisioBlend, a unified framework that enables 3D control over image synthesis from sketches and strokes based on diffusion models. The framework allows users to decide the level of faithfulness to input strokes and sketches, achieving state-of-the-art performance in terms of realism and flexibility. VisioBlend solves the problem of data availability by synthesizing new data points from hand-drawn sketches and strokes, enriching the dataset and enabling more robust and diverse image synthesis. This work showcases the power of diffusion models in image creation, offering a user-friendly and versatile approach for turning artistic visions into reality. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary VisioBlend is a special computer program that helps turn drawings into realistic images. It’s like having an artist’s imagination come to life! The researchers created this tool using something called “diffusion models”. This means they can make lots of different pictures from just a few simple sketches. They also figured out how to use this technology to create new data points, which makes the whole process even better. |
Keywords
» Artificial intelligence » Diffusion » Image synthesis
