Diffusion Model Based Facial Anonymization in TinyML setup
- Project
- 20219 IML4E
- Type
- Enhancement
- Description
Slightly improved generated image quality and much improved generation performance in terms of wall clock time on TinyML devices. Github: https://github.com/balazsmorv/facediffusion
- Contact
- Balázs Tibor Morvay
- morvayb@edu.bme.hu
- Research area(s)
- Anonymization, Privacy
- Technical features
Machine learning pipeline consisting of a diffusion implicit model and an image super resolution model, to anonymize faces in images.
- Integration constraints
Python environment, specified packages
- Targeted customer(s)
Dataset curators that are looking for ways to anonymize a dataset
- Conditions for reuse
MIT Licence
- Confidentiality
- Public
- Publication date
- 02-05-2024
- Involved partners
- Budapest University of Technology and Economics (HUN)