10 citations · 32 across the 9 of their papers we have counts for
9 papers
4Dynamic: Text-to-4D Generation with Hybrid Priors
Yu-Jie Yuan, Leif Kobbelt, Jiwen Liu +4
Due to the fascinating generative performance of text-to-image diffusion models, growing text-to-3D generation works explore distilling the 2D generative priors into 3D, using the…
Recent Advances in 3D Gaussian Splatting
Tong Wu, Yu-Jie Yuan, Ling-Xiao Zhang +4
The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Field…
Mesh-based Gaussian Splatting for Real-time Large-scale Deformation
Lin Gao, Jie Yang, Bo-Tao Zhang +4
Neural implicit representations, including Neural Distance Fields and Neural Radiance Fields, have demonstrated significant capabilities for reconstructing surfaces with complicate…
Point2Mask: Point-supervised Panoptic Segmentation via Optimal Transport
Wentong Li, Yuqian Yuan, Song Wang +4
Weakly-supervised image segmentation has recently attracted increasing research attentions, aiming to avoid the expensive pixel-wise labeling. In this paper, we present an effectiv…
StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning
Yi-Hua Huang, Yue He, Yu-Jie Yuan +2
3D scene stylization aims at generating stylized images of the scene from arbitrary novel views following a given set of style examples, while ensuring consistency when rendered fr…
NeRF-Editing: Geometry Editing of Neural Radiance Fields
Yu-Jie Yuan, Yang-Tian Sun, Yu-Kun Lai +3
Implicit neural rendering, especially Neural Radiance Field (NeRF), has shown great potential in novel view synthesis of a scene. However, current NeRF-based methods cannot enable…
A Revisit of Shape Editing Techniques: from the Geometric to the Neural Viewpoint
Yu-Jie Yuan, Yu-Kun Lai, Tong Wu +2
3D shape editing is widely used in a range of applications such as movie production, computer games and computer aided design. It is also a popular research topic in computer graph…
TM-NET: Deep Generative Networks for Textured Meshes
Lin Gao, Tong Wu, Yu-Jie Yuan +3
We introduce TM-NET, a novel deep generative model for synthesizing textured meshes in a part-aware manner. Once trained, the network can generate novel textured meshes from scratc…
Mesh Variational Autoencoders with Edge Contraction Pooling
Yu-Jie Yuan, Yu-Kun Lai, Jie Yang +2
3D shape analysis is an important research topic in computer vision and graphics. While existing methods have generalized image-based deep learning to meshes using graph-based conv…