activity
20182022
most citedParametric Reshaping of Portraits in Videos

4 citations · 4 across the 1 of their papers we have counts for

collaborators

6 papers

cs.GR2025

Learning Conjugate Direction Fields for Planar Quadrilateral Mesh Generation

Jiong Tao, Yong-Liang Yang, Bailin Deng

Planar quadrilateral (PQ) mesh generation is a key process in computer-aided design, particularly for architectural applications where the goal is to discretize a freeform surface…

cs.CV20224 cited

Parametric Reshaping of Portraits in Videos

Xiangjun Tang, Wenxin Sun, Yong-Liang Yang +1

Sharing short personalized videos to various social media networks has become quite popular in recent years. This raises the need for digital retouching of portraits in videos. How…

cs.CV2020

BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images

Thu Nguyen-Phuoc, Christian Richardt, Long Mai +2

We present BlockGAN, an image generative model that learns object-aware 3D scene representations directly from unlabelled 2D images. Current work on scene representation learning e…

cs.CV2019

Rank3DGAN: Semantic mesh generation using relative attributes

Yassir Saquil, Qun-Ce Xu, Yong-Liang Yang +1

In this paper, we investigate a novel problem of using generative adversarial networks in the task of 3D shape generation according to semantic attributes. Recent works map 3D shap…

cs.CV2019

HoloGAN: Unsupervised learning of 3D representations from natural images

Thu Nguyen-Phuoc, Chuan Li, Lucas Theis +2

We propose a novel generative adversarial network (GAN) for the task of unsupervised learning of 3D representations from natural images. Most generative models rely on 2D kernels t…

cs.CV2018

RenderNet: A deep convolutional network for differentiable rendering from 3D shapes

Thu Nguyen-Phuoc, Chuan Li, Stephen Balaban +1

Traditional computer graphics rendering pipeline is designed for procedurally generating 2D quality images from 3D shapes with high performance. The non-differentiability due to di…