Project Overview

Semantic Facial Image Manipulation is a conditional generation task. It opens the door to many exciting applications in different areas, including the movie industry, photography technologies, fashion and e-commerce business. The goal is to synthesize a facial image conditioned on both the identity and expression.

This project aims at generating 2D photo-realistic facial images with accurate target expression labeled in FACS coding guided by 3D information. It can be applied to tasks like expression recognition and FACS data generation.

Team

Zhuoqian Yang

Zhuoqian is an MSCV student of class Fall 2019. He received his bachelor’s degree in Software Engineering from Beihang University. His research interest is in creative computer vision, content creation and manipulation with generative models and unsupervised/self-supervised learning.

Responsibilities: Experimenting with the manipulation of 3D facial geometry via a 2.5D representation.

Dai Li

Dai is an MSCV student of class Fall 2019. She received her bachelor’s degree in Department of Automation from Tsinghua University. Her research focuses on object detection, semantic segmentation and network interpretability.

Responsibilities: Experimenting with neural rendering via manipulations in feature space.

Advisor: Laszlo Jeni

Laszlo is a Systems Scientist (faculty) in the Robotics Institute at Carnegie-Mellon University. I focus on advancing the state-of-the-art in multi-modal methods for computational behavior science, specifically in areas of modelling, analysis, and synthesis of human behavior and emotion using diverse sensors.