24 citations · 53 across the 6 of their papers we have counts for
10 papers · 1 filter
Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation
Xiaofeng Liu, Fangxu Xing, Chao Yang +2
Unsupervised domain adaptation (UDA) aims to transfer knowledge learned from a labeled source domain to an unlabeled and unseen target domain, which is usually trained on data from…
One-Shot Domain Adaptation For Face Generation
Chao Yang, Ser-Nam Lim
In this paper, we propose a framework capable of generating face images that fall into the same distribution as that of a given one-shot example. We leverage a pre-trained StyleGAN…
Towards Disentangled Representations for Human Retargeting by Multi-view Learning
Chao Yang, Xiaofeng Liu, Qingming Tang +1
We study the problem of learning disentangled representations for data across multiple domains and its applications in human retargeting. Our goal is to map an input image to an id…
Unconstrained Facial Expression Transfer using Style-based Generator
Chao Yang, Ser-Nam Lim
Facial expression transfer and reenactment has been an important research problem given its applications in face editing, image manipulation, and fabricated videos generation. We p…
Dependency-aware Attention Control for Unconstrained Face Recognition with Image Sets
Xiaofeng Liu, B. V. K Vijaya Kumar, Chao Yang +2
This paper targets the problem of image set-based face verification and identification. Unlike traditional single media (an image or video) setting, we encounter a set of heterogen…
Show, Attend and Translate: Unsupervised Image Translation with Self-Regularization and Attention
Chao Yang, Taehwan Kim, Ruizhe Wang +2
Image translation between two domains is a class of problems aiming to learn mapping from an input image in the source domain to an output image in the target domain. It has been a…