TikTok’s Non-Inclusive Beauty Algorithm & Why We Should Care

This project will be a meta-analysis of how the popular social media app known as TikTok takes into account image recognition in their machine learning algorithms through the data it analyzes from its users. It will also see how it identifies and pushes the most beautiful to fame and virality. Though we don’t have access to the actual Tiktok algorithm, we are going to use a very similar dataset known as SCUT-FBP5500. We will analyze how it perpetuates toxic western and eastern beauty standards that are only based on far too simple analyses of what is considered beautiful. We will also use a separate study through a scientific study, which analyzes men and women stimulus in response to beauty. We will lastly use an article, which explores the Chinese app called Alipay, and how it uses beauty filters that perpetuate patriarchal ideals over women. This dataset, study, and article will uncover how human nature and sociology can contribute to how algorithms are truly being fed our want to see idealistic beauty. They will also prove how the belief that the algorithm is inherently bad is false, but that human society around the world needs new establishments of what true beauty is instead. Overall, the goal of this project is to understand these examples of beauty algorithms, how they work, the reason they are used in human society, and how we can improve or discourage use of them in our social media apps

Facial Beauty Prediction and Analysis based on Deep Convolutional Neural Network: A Review

Abstract: Facial attractiveness or facial beauty prediction (FBP) is a current study that has several potential usages. It is a key difficulty area in the computer vision domain because of the few public databases related to FBP and its experimental trials on the minor-scale database. Moreover, the evaluation of facial beauty is personalized in nature, with people having personalized favor of beauty. Deep learning techniques have displayed a significant ability in terms of analysis and feature representation. The previous studies focussed on scattered portions of facial beauty with fewer comparisons between diverse techniques. Thus, this article reviewed the recent research on computer prediction and analysis of face beauty based on deep convolution neural network DCNN. Furthermore, the provided possible lines of research and challenges in this article can help researchers in advancing the state – of- art in future work