학술논문

Improving Key Human Features for Pose Transfer
Document Type
Conference
Source
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) ICCVW Computer Vision Workshops (ICCVW), 2021 IEEE/CVF International Conference on. :1963-1972 Oct, 2021
Subject
Computing and Processing
Computer vision
Annotations
Computational modeling
Conferences
Task analysis
Faces
Language
ISSN
2473-9944
Abstract
It is still a great challenge in the Pose Transfer task to generate visually coherent images, to preserve the texture of clothes, to maintain the source identity and to realistically generate key human features such as the face or the hands. To tackle these challenges, we first conduct a study to obtain the most robust conditioning labels for this task and the baseline method [44] that we choose. We then improve upon the baseline by including deep source features from an Auto-encoder through an Attention mechanism. Finally we add region discriminators that are focused on key human features, thus obtaining results competitive with the state-of-the-art.