Comprehensive Facial Expression Synthesis using Human-Interpretable Language

TL;DR

This paper introduces a novel facial expression synthesis model that uses natural language descriptions to generate detailed facial images, enabling intuitive control over facial movements and expressions.

Contribution

It presents a new approach that leverages human-friendly language descriptions for more intuitive and detailed facial expression synthesis, improving interpretability and control.

Findings

Effective synthesis of detailed facial expressions from language descriptions

Ability to control individual facial movements via specific words

Outperforms existing methods in qualitative and quantitative evaluations

Abstract

Recent advances in facial expression synthesis have shown promising results using diverse expression representations including facial action units. Facial action units for an elaborate facial expression synthesis need to be intuitively represented for human comprehension, not a numeric categorization of facial action units. To address this issue, we utilize human-friendly approach: use of natural language where language helps human grasp conceptual contexts. In this paper, therefore, we propose a new facial expression synthesis model from language-based facial expression description. Our method can synthesize the facial image with detailed expressions. In addition, effectively embedding language features on facial features, our method can control individual word to handle each part of facial movement. Extensive qualitative and quantitative evaluations were conducted to verify the effectiveness of the natural language.