53 citations · 270 across the 45 of their papers we have counts for
6 papers · 1 filter
Mesh Guided One-shot Face Reenactment using Graph Convolutional Networks
Guangming Yao, Yi Yuan, Tianjia Shao +1
Face reenactment aims to animate a source face image to a different pose and expression provided by a driving image. Existing approaches are either designed for a specific identity…
Second-order Neural Network Training Using Complex-step Directional Derivative
Siyuan Shen, Tianjia Shao, Kun Zhou +3
While the superior performance of second-order optimization methods such as Newton's method is well known, they are hardly used in practice for deep learning because neither assemb…
Dynamic Future Net: Diversified Human Motion Generation
Wenheng Chen, He Wang, Yi Yuan +2
Human motion modelling is crucial in many areas such as computer graphics, vision and virtual reality. Acquiring high-quality skeletal motions is difficult due to the need for spec…
AutoSweep: Recovering 3D Editable Objectsfrom a Single Photograph
Xin Chen, Yuwei Li, Xi Luo +4
This paper presents a fully automatic framework for extracting editable 3D objects directly from a single photograph. Unlike previous methods which recover either depth maps, point…
Unsupervised Facial Action Unit Intensity Estimation via Differentiable Optimization
Xinhui Song, Tianyang Shi, Tianjia Shao +3
The automatic intensity estimation of facial action units (AUs) from a single image plays a vital role in facial analysis systems. One big challenge for data-driven AU intensity es…
Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks
Jiangke Lin, Yi Yuan, Tianjia Shao +1
3D Morphable Model (3DMM) based methods have achieved great success in recovering 3D face shapes from single-view images. However, the facial textures recovered by such methods lac…