This repository contains the textual inversion adaptation weights for
stabilityai/stable-diffusion-2-1-base learned for the disease concept of
folliculitis (
<folliculitis-class>).
It is part of the
cgDDI (
Controllable
Generation of
Diverse
Dermatological
Imagery) framework presented in the paper
Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification.
Please refer to the official
GitHub notebooks for detailed instructions on textual inversion pipeline setups, LoRA training, and semantic sampling using the learned concept
<folliculitis-class>.
1@inproceedings{carrion2026cgddi,
2 title = {Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification},
3 author = {Carri{\'o}n, H{\'e}ctor and Norouzi, Narges},
4 booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
5 year = {2026},
6 publisher = {Springer},
7 series = {Lecture Notes in Computer Science}
8}