Wuziyi616/SlotDiffusion
Code release for NeurIPS 2023 paper SlotDiffusion: Object-centric Learning with Diffusion Models
This project helps researchers and developers working with computer vision automatically identify and isolate distinct objects within images and video without needing extensive manual labeling. It takes raw images or video frames and outputs segmented objects, which are then used for tasks like image editing or video prediction. This is for AI/ML researchers, computer vision engineers, and data scientists developing new object recognition and scene understanding applications.
No commits in the last 6 months.
Use this if you need to perform unsupervised object segmentation, image editing, or compositional generation from visual data, especially for research and development of new computer vision models.
Not ideal if you are looking for an off-the-shelf application for immediate production use or do not have access to a Slurm GPU cluster.
Stars
94
Forks
11
Language
Python
License
MIT
Category
Last pushed
Jan 16, 2024
Commits (30d)
0
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