activity
20202022
most citedDeep Generation of Face Images from Sketches

4 citations · 7 across the 3 of their papers we have counts for

collaborators

5 papers

cs.GR20222 cited

NeRFFaceEditing: Disentangled Face Editing in Neural Radiance Fields

Kaiwen Jiang, Shu-Yu Chen, Feng-Lin Liu +2

Recent methods for synthesizing 3D-aware face images have achieved rapid development thanks to neural radiance fields, allowing for high quality and fast inference speed. However,…

cs.GR20221 cited

DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN

Wanchao Su, Hui Ye, Shu-Yu Chen +2

The research topic of sketch-to-portrait generation has witnessed a boost of progress with deep learning techniques. The recently proposed StyleGAN architectures achieve state-of-t…

cs.GR2021

DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control

Shu-Yu Chen, Feng-Lin Liu, Yu-Kun Lai +4

Recent facial image synthesis methods have been mainly based on conditional generative models. Sketch-based conditions can effectively describe the geometry of faces, including the…

cs.GR20204 cited

Deep Generation of Face Images from Sketches

Shu-Yu Chen, Wanchao Su, Lin Gao +2

Recent deep image-to-image translation techniques allow fast generation of face images from freehand sketches. However, existing solutions tend to overfit to sketches, thus requiri…

cs.CV2020

Deep Line Art Video Colorization with a Few References

Min Shi, Jia-Qi Zhang, Shu-Yu Chen +3

Coloring line art images based on the colors of reference images is an important stage in animation production, which is time-consuming and tedious. In this paper, we propose a dee…