activity
20142025
most citedBlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images

109 citations · 191 across the 13 of their papers we have counts for

collaborators

14 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.CV2023★ 1 cited

Neural 3D Strokes: Creating Stylized 3D Scenes with Vectorized 3D Strokes

Hao-Bin Duan, Miao Wang, Yan-Xun Li +1

We present Neural 3D Strokes, a novel technique to generate stylized images of a 3D scene at arbitrary novel views from multi-view 2D images. Different from existing methods which…

cs.CV2023

Enhancing the Authenticity of Rendered Portraits with Identity-Consistent Transfer Learning

Luyuan Wang, Yiqian Wu, Yongliang Yang +2

Despite rapid advances in computer graphics, creating high-quality photo-realistic virtual portraits is prohibitively expensive. Furthermore, the well-know ''uncanny valley'' effec…

cs.CV2023★ 3 cited

GRIG: Few-Shot Generative Residual Image Inpainting

Wanglong Lu, Xianta Jiang, Xiaogang Jin +5

Image inpainting is the task of filling in missing or masked region of an image with semantically meaningful contents. Recent methods have shown significant improvement in dealing…

cs.CV2022★ 2 cited

Gradient-based Point Cloud Denoising with Uniformity

Tian-Xing Xu, Yuan-Chen Guo, Yong-Liang Yang +1

Point clouds captured by depth sensors are often contaminated by noises, obstructing further analysis and applications. In this paper, we emphasize the importance of point distribu…

cs.CV2022★ 4 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.CV2022★ 7 cited

Do Inpainting Yourself: Generative Facial Inpainting Guided by Exemplars

Wanglong Lu, Hanli Zhao, Xianta Jiang +5

We present EXE-GAN, a novel exemplar-guided facial inpainting framework using generative adversarial networks. Our approach can not only preserve the quality of the input facial im…

cs.CV2020★ 109 cited

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★ 1 cited

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★ 63 cited

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…

cs.CV2018

Physics-driven Fire Modeling from Multi-view Images

Gara Dorta, Luca Benedetti, Dmitry Kit +1

Fire effects are widely used in various computer graphics applications such as visual effects and video games. Modeling the shape and appearance of fire phenomenon is challenging a…

cs.CG2015★ 1 cited

Computational Network Design from Functional Specifications

Chi-Han Peng, Niloy J. Mitra, Fan Bao +2

Connectivity and layout of underlying networks largely determine the behavior of many environments. For example, transportation networks determine the flow of traffic in cities, or…

cs.GR2014

Mesh2Fab: Reforming Shapes for Material-specific Fabrication

Yong-Liang Yang, Jun Wang, Niloy J. Mitra

As humans, we regularly associate shape of an object with its built material. In the context of geometric modeling, however, this interrelation between form and material is rarely…