custom-diffusion and Collaborative-Diffusion

custom-diffusion
51
Established
Maintenance 6/25
Adoption 10/25
Maturity 16/25
Community 19/25
Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 15/25
Stars: 1,971
Forks: 142
Downloads:
Commits (30d): 0
Language: Python
License:
Stars: 438
Forks: 38
Downloads:
Commits (30d): 0
Language: Python
License:
No Package No Dependents
Stale 6m No Package No Dependents

About custom-diffusion

adobe-research/custom-diffusion

Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)

This tool helps designers, marketers, and artists create unique images by teaching an AI model about new objects, styles, or concepts from just a few example pictures. You provide 4-20 images of something new, like a specific product or an artistic style, and then you can generate new images incorporating that concept using text prompts. It's designed for anyone who needs to quickly generate custom visual content featuring specific items or aesthetics.

generative-art product-visualization digital-marketing content-creation graphic-design

About Collaborative-Diffusion

ziqihuangg/Collaborative-Diffusion

[CVPR 2023] Collaborative Diffusion

This project helps graphic designers, content creators, and marketing professionals generate and edit human faces using a combination of text descriptions and segmentation masks. You provide textual prompts (like "a man in his thirties with a beard") and/or visual masks specifying facial features, and it produces high-quality face images that match your detailed input. It's designed for users who need precise control over synthetic face imagery.

digital art image generation character design marketing content visual media production

Scores updated daily from GitHub, PyPI, and npm data. How scores work