most citedQuantifying Facial Age by Posterior of Age Comparisons

13 citations · 31 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2019

Delving Deep Into Hybrid Annotations for 3D Human Recovery in the Wild

Yu Rong, Ziwei Liu, Cheng Li +2

Though much progress has been achieved in single-image 3D human recovery, estimating 3D model for in-the-wild images remains a formidable challenge. The reason lies in the fact tha…

cs.CV2019

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…

cs.CV20194 cited

Disentangling Content and Style via Unsupervised Geometry Distillation

Wayne Wu, Kaidi Cao, Cheng Li +2

It is challenging to disentangle an object into two orthogonal spaces of content and style since each can influence the visual observation differently and unpredictably. It is rare…

cs.CV201910 cited

TransGaGa: Geometry-Aware Unsupervised Image-to-Image Translation

Wayne Wu, Kaidi Cao, Cheng Li +2

Unsupervised image-to-image translation aims at learning a mapping between two visual domains. However, learning a translation across large geometry variations always ends up with…

cs.CV2019

Deep Comprehensive Correlation Mining for Image Clustering

Jianlong Wu, Keyu Long, Fei Wang +4

Recent developed deep unsupervised methods allow us to jointly learn representation and cluster unlabelled data. These deep clustering methods mainly focus on the correlation among…

cs.CV201713 cited

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…