yinboc/infd
Image Neural Field Diffusion Models, CVPR 2024 (Highlight)
This project helps researchers and practitioners in computer vision generate realistic, high-resolution images. It takes a collection of existing images, such as a dataset of faces, and learns to create entirely new, diverse images that look very similar to the originals but are not exact copies. Computer vision researchers and AI artists would find this useful for expanding datasets or creating novel visual content.
No commits in the last 6 months.
Use this if you need to generate high-fidelity, photorealistic images from scratch based on a given dataset, particularly for research or content creation.
Not ideal if you need to perform image editing, style transfer, or other image manipulations on existing images, rather than generating new ones.
Stars
80
Forks
3
Language
Python
License
BSD-3-Clause
Category
Last pushed
Nov 08, 2024
Commits (30d)
0
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