chen-hao-chao/dlsm
[ICLR 2022] Denoising Likelihood Score Matching for Conditional Score-based Data Generation
This project provides the tools to generate new, high-quality synthetic images based on existing image datasets. You can input a collection of images, specify conditions or categories, and receive a set of newly created images that resemble the originals but are entirely unique. This is ideal for researchers, data scientists, or machine learning engineers working on image synthesis and conditional data generation tasks.
No commits in the last 6 months.
Use this if you need to create diverse, realistic synthetic images conditioned on specific attributes or categories from an existing dataset for research or augmentation.
Not ideal if you are looking for a simple, out-of-the-box image generation tool without diving into model training and evaluation.
Stars
11
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 02, 2025
Commits (30d)
0
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