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Interactive NeRF Geometry Editing With Shape Priors 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 12, 页码: 14821-14837
作者:  Yuan, Yu-Jie;  Sun, Yang-Tian;  Lai, Yu-Kun;  Ma, Yuewen;  Jia, Rongfei;  Kobbelt, Leif;  Gao, Lin
收藏  |  浏览/下载：2/0  |  提交时间：2024/05/20
Neural radiance fields  geometry editing  shape deformation  interactive editing  
Neural Radiance Fields From Sparse RGB-D Images for High-Quality View Synthesis 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 7, 页码: 8713-8728
作者:  Yuan, Yu-Jie;  Lai, Yu-Kun;  Huang, Yi-Hua;  Kobbelt, Leif;  Gao, Lin
收藏  |  浏览/下载：7/0  |  提交时间：2023/12/04
Novel view synthesis  neural rendering  neural radiance fields  
SceneHGN: Hierarchical Graph Networks for 3D Indoor Scene Generation With Fine-Grained Geometry 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 7, 页码: 8902-8919
作者:  Gao, Lin;  Sun, Jia-Mu;  Mo, Kaichun;  Lai, Yu-Kun;  Guibas, Leonidas J.;  Yang, Jie
收藏  |  浏览/下载：7/0  |  提交时间：2023/12/04
3Dindoor scene synthesis  deep generative model  fine-grained mesh generation  graph neural network  recursive neural network  relationship graphs  variational autoencoder  
Multiscale Mesh Deformation Component Analysis With Attention-Based Autoencoders 期刊论文
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2023, 卷号: 29, 期号: 2, 页码: 1301-1317
作者:  Yang, Jie;  Gao, Lin;  Tan, Qingyang;  Huang, Yi-Hua;  Xia, Shihong;  Lai, Yu-Kun
收藏  |  浏览/下载：13/0  |  提交时间：2023/07/12
Multi-scale  shape analysis  attention mechanism  sparse regularization  stacked auto-encoder  
Variational Autoencoders for Localized Mesh Deformation Component Analysis 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 卷号: 44, 期号: 10, 页码: 6297-6310
作者:  Tan, Qingyang;  Zhang, Ling-Xiao;  Yang, Jie;  Lai, Yu-Kun;  Gao, Lin
收藏  |  浏览/下载：27/0  |  提交时间：2022/12/07
Strain  Shape  Three-dimensional displays  Principal component analysis  Geometry  Convolution  Solid modeling  3D meshes  variational autoencoder  graph convolution  sparsity regularization  
NET: Deep Generative Networks for Textured Meshes 期刊论文
ACM TRANSACTIONS ON GRAPHICS, 2021, 卷号: 40, 期号: 6, 页码: 15
作者:  Gao, Lin;  Wu, Tong;  Yu-Jie Yuan;  Ming-Xian Lin;  Yu-Kun Lai;  Zhang, Hao
收藏  |  浏览/下载：18/0  |  提交时间：2022/12/07
Mesh representation  Mesh texture  Shape generation  
DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control 期刊论文
ACM TRANSACTIONS ON GRAPHICS, 2021, 卷号: 40, 期号: 4, 页码: 15
作者:  Chen, Shu-Yu;  Liu, Feng-Lin;  Lai, Yu-Kun;  Rosin, Paul L.;  Li, Chunpeng;  Fu, Hongbo;  Gao, Lin
收藏  |  浏览/下载：38/0  |  提交时间：2021/12/01
Deep image generation  face editing  image disentangling  sketch-based interfaces  
PRS-Net: Planar Reflective Symmetry Detection Net for 3D Models 期刊论文
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2021, 卷号: 27, 期号: 6, 页码: 3007-3018
作者:  Gao, Lin;  Zhang, Ling-Xiao;  Meng, Hsien-Yu;  Ren, Yi-Hui;  Lai, Yu-Kun;  Kobbelt, Leif
收藏  |  浏览/下载：38/0  |  提交时间：2021/12/01
Three-dimensional displays  Shape  Geometry  Two dimensional displays  Feature extraction  Solid modeling  Computational modeling  Unsupervised learning  convolutional neural network  symmetry detection  3D models  planar reflective symmetry  
Sparse Data Driven Mesh Deformation 期刊论文
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2021, 卷号: 27, 期号: 3, 页码: 2085-2100
作者:  Gao, Lin;  Lai, Yu-Kun;  Yang, Jie;  Zhang, Ling-Xiao;  Xia, Shihong;  Kobbelt, Leif
收藏  |  浏览/下载：36/0  |  提交时间：2021/12/01
Strain  Shape  Deformable models  Interpolation  Computational modeling  Geometry  Manifolds  Data driven  sparsity  large scale deformation  real-time deformation  
A survey on deep geometry learning: From a representation perspective 期刊论文
COMPUTATIONAL VISUAL MEDIA, 2020, 卷号: 6, 期号: 2, 页码: 113-133
作者:  Xiao, Yun-Peng;  Lai, Yu-Kun;  Zhang, Fang-Lue;  Li, Chunpeng;  Gao, Lin
收藏  |  浏览/下载：32/0  |  提交时间：2021/12/01
3D shape representation  geometry learning  neural networks  computer graphics