QOVES is a facial aesthetics consultancy dedicated to answering the age-old question of what makes a face attractive through modern science and machine learning.
Understanding the Science of Beauty
Get tailored aesthetics advice from our trained team of medical professionals and consultants
We develop tools to tackle racial beauty biases in AI to foster greater inclusivity in beauty research
Facial Aesthetics Assessment
Whether you’re seriously considering surgery or just curious about potential non-surgical improvements to your looks, the Aesthetics report evaluates your face with our team of aesthetic, dental, orthodontic and medical consultants, applying the scientific literature to your face.
- Cephalometric Averageness
- How your features compare to research averages
- Facial Proportions
- Establishing the harmony between features
- Dentofacial Assessment
- Lip, mouth, teeth and smile aesthetic
- Frontal Profile Assessment
- Eye, midface and jaw proportion
- Side Profile Assessment
- Lower, underjaw, eye and ear proportion
- Side Profile Morph
- A Photoshopped morph of how you may look with the changes
Get a broad range of expert aesthetics advice under one roof
Introducing QOVES Laboratory
All of our current and upcoming facial AI projects are now hosted on our QOVES laboratory subdomain. Below are some projects we have in the pipeline for this year.
There is a serious lack of ethnic diversity in Machine Learning datasets
Biased data produces biases results
There is an undeniably strong bias towards Caucasian faces in just about any currently existing Machine Learning (ML) algorithm, from CNN classifiers to GAN generators. A recent study by Karkkainen and colleague found that Hispanic and Middle Eastern ethnicities were greatly underrepresented in most existing ML datasets,
with Black and South Asian ethnicities being not too far behind. This bias in ML is common knowledge and has heavily stigmatized the large majority of AI research to the general public, especially with anything that claims to look at beauty as objectively as possible.
Full Writeup - Coming Soon
At QOVES, we’re working on a novel approach to develop larger ethnic datasets using existing computer generated faces through a process of CNN classification by facial features and then morphing them together to control phenotype expression. The end goal is to develop a sizable dataset, segmented for every living ethnicity to improve parity and fairness in the ML field.
Get accurate diagnosis and feedback on your cosmetic condition in realtime
Bringing dermatology into A.I.
Based on our prototype facial assessment tool which uses a similar CNN (convolutional neural network) to classify 17 different cosmetic conditions, this version 2 will feature improved accuracy with much better diagnostic feedback and transparency. Our version 2 will use a newer image segmentation model to split key regions of the face apart
to be assessed individually to healthy examples, providing much more accurate results. Version 1 used a holistic evaluation which looked at the face as a whole. As always, it will feature an ethnically diverse training protocol.
Full Writeup - Coming Soon
Hairstyle recommendations based on your facial features
Storing a hairdresser’s lifetime into a ML algorithm
Using the current research literature on face shape detection, we’ve devised a novel approach to recommending the right hairstyle for faces based on face shape, hair and skin texture and androgenicity. In doing so, users can not only try on different
hairstyles using a StyleGAN approach of morphing a target face with the desired hair with the users, but they will also be provided with the correct aesthetic recommendations so that the process of finding a suitable hairstyle is less based on trial and error.
Learn about facial aesthetics and A.I. with us
A weekly podcast on the latest research regarding what makes a face attractive, discussions on AI ethics & biases and how this applies to you.
Near daily uploads on beauty, surgery, anthropology and psychology research to teach our audiences the basics of what we do and what to look for.