13 citations · 15 across the 2 of their papers we have counts for
4 papers
One-shot Face Reenactment
Yunxuan Zhang, Siwei Zhang, Yue He +3
To enable realistic shape (e.g. pose and expression) transfer, existing face reenactment methods rely on a set of target faces for learning subject-specific traits. However, in rea…
CMR motion artifact correction using generative adversarial nets
Yunxuan Zhang, Weiliang Zhang, Qinyan Zhang +3
Cardiovascular Magnetic Resonance (CMR) plays an important role in the diagnoses and treatment of cardiovascular diseases while motion artifacts which are formed during the scannin…
ReenactGAN: Learning to Reenact Faces via Boundary Transfer
Wayne Wu, Yunxuan Zhang, Cheng Li +2
We present a novel learning-based framework for face reenactment. The proposed method, known as ReenactGAN, is capable of transferring facial movements and expressions from monocul…
Quantifying Facial Age by Posterior of Age Comparisons
Yunxuan Zhang, Li Liu, Cheng Li +1
We introduce a novel approach for annotating large quantity of in-the-wild facial images with high-quality posterior age distribution as labels. Each posterior provides a probabili…