# MicroGlam: Microscopic Skin Image Dataset with Cosmetics

arXiv: https://arxiv.org/abs/2401.05339 · HTML: https://mlsanity.com/paper/2401.05339/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 10 references that are in the map.
- First posted on arXiv 29 Nov 2023.

## Builds on (most cited first, 2 of 2)

- [LADN: Local Adversarial Disentangling Network for Facial Makeup and De-Makeup](https://mlsanity.com/paper/1904.11272/) (2019)
- [Makeup Extraction of 3D Representation via Illumination-Aware Image Decomposition](https://mlsanity.com/paper/2302.13279/) (2023)

## Abstract (arXiv)

In this paper, we present a cosmetic-specific skin image dataset. It consists of skin images from 45 patches (5 skin patches each from 9 participants) of size 8mm^*8mm under three cosmetic products (i.e., foundation, blusher, and highlighter). We designed a novel capturing device inspired by Light Stage. Using the device, we captured over 600 images of each skin patch under diverse lighting conditions in 30 seconds. We repeated the process for the same skin patch under three cosmetic products. Finally, we demonstrate the viability of the dataset with an image-to-image translation-based pipeline for cosmetic rendering and compared our data-driven approach to an existing cosmetic rendering method.