Face Beauty Papers

Paper #1 - FabSoften: Face Beautification via Dynamic Skin Smoothing, Guided Feathering, and Texture Restoration

Key Notes

• Softening is carried out by an attribute-aware dynamic smoothing filter
• YouCam, B612 and ModiFace
• Smoothing blemishes in the facial region, including wrinkles, spots, patchy reflections, and skin nonuniformities.

Related Work

• Edge-Aware Smoothing Filters; 
• Layer Decomposition Based Approaches; 
• Deep Learning-Based Approaches; 
• Generative Models

• To detect blemishes in the skin region, we first employ the Canny Edge detector [6] to localize strong edge patterns

Skin-mask generation algorithms generally fall into three broad categories:

• Color pixel classification 
• Gaussian Mixture Model
• Mutually Guided Image Filtering (muGIF) 
• Fast Global Smoothing filter (FGS)

Guided Filter Python Code

• We crop zoomed-in portions of the image to highlight each method’s performance on skin texture retainment and preserving hair regions

Fabsoften Key Features

• Preprocessing
• Landmark Detection
• Binary Skin Mask
• Blemish Detection and Concealment
• Skin Mask Generation and Refinement
• GMM Clustering (#6)

Segmentation?

•  Guided Feathering (pending)
•  Skin Imperfection Smoothing
•  Dynamic Mean Filter
•  Attribute-aware Dynamic Guided Filter
•  Skin Texture Restoration (Wavelet-based STR)

BeautyGAN

Facebeauty

Beautyfinder

Face Smoothing: Detection and Beautification

• Change image from BGR to HSV colorspace
• Create mask of HSV image
• Apply a bilateral filter to the Region of Interest
• Apply filtered ROI back to original image

Guided Filter - Simple Python implementation of paper:

Face beautification algorithm

Paper - Face Beautification and Color Enhancement with Scene Mode Detection

• A bilateral filter is an edge-preserving smoothing filter.
• Contrast enhancement methods can produce strong effect on local contrast enhancement
• Gaussian Blur of space and intensity of each pixel
• Automatically detect the best-match scene mode for input image. 

BEHOLDER-GAN: GENERATION AND BEAUTIFICATION OF FACIAL IMAGES WITH CONDITIONING ON THEIR BEAUTY LEVEL

• Given an image x and the pre-trained generator G, we want to recover the corresponding latent vector z and beauty score β

Face Beautification: Beyond Makeup Transfer

More Reads

• LFW-Beautified: A Dataset of Face Images with Beautification and Augmented Reality Filters
• Transferring Rich Deep Features for Facial Beauty Prediction
• Facial Landmarks and Face Filter using OpenCV Python

Keep Exploring!!!