109 citations · 191 across the 13 of their papers we have counts for
11 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…