Jie Yang's Homepage (ICT, UCAS)

Jie Yang

Ph.D.

No. 6 Kexueyuan South Road, Haidian District,
Beijing, P.R. China, 100190

Email: yangjie01 AT ict dot ac dot cn

Google Scholar | dblp | Github

Biography

I am a Ph.D. student at the Institute of Computing Technology, Chinese Academy of Sciences . I have received a mathematics bachelor's degree from Sichuan University in 2016. Currently, I focus on geometry learning under the supervision of Prof. Lin Gao and Prof. Shihong Xia.

My research interest includes geometry processing, computer graphics, and deep learning. Here is my resume. If you are interested in my research or potential collaborations, please feel free to contact me.

News

Sep. 2021: One paper gets acceptance to NeurIPS 2021.
Sep. 2021: Two papers get acceptance to IEEE TVCG.
Jul. 2021: One paper gets acceptance to ICCV 2021.
Jun. 2021: One paper has published at IEEE TPAMI 2021.
Aug. 2020: Our paper Learning on 3D Meshes with Laplacian Encoding and Pooling receives an acceptence from IEEE TVCG.
Apr. 2020: Our paper Mesh Variational Autoencoders with Edge Contraction Pooling is accepted by IEEE CVPR WorkShop (Learning 3D Generative Models).
Aug. 2019: Our paper Sparse Data Driven Mesh Deformation is accepted by IEEE TVCG.
Jul. 2019: Our paper SDM-NET is conditionally accepted by Siggraph Asia 2019.
Jul. 2019: Our paper Sparse Data Driven Mesh Deformation is reveived minor revision from TVCG.
Sep. 2018: Our paper Automatic Unpaired Shape Deformation Transfer is accepted to SIGGRAPH ASIA 2018.
Apr. 2018: Our paper Biharmonic deformation transfer with automatic key point selection is accepted to Graphical Models.
Sep. 2017: Our paper Mesh-based Autoencoders for Localized Deformation Component Analysis is accepted to AAAI 2018.

Publications

	OctField: Hierarchical Implicit Functions for 3D Modeling Jia-Heng Tang^#, Weikai Chen^#, Jie Yang, Bo Wang, Songrun Liu, Bo Yang and Lin Gao^* The Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS), 2021 [Paper] [Project]
	Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning Mingxian Lin, Jie Yang, He Wang, Yu-Kun Lai, Rongfei Jia, Binqiang Zhao and Lin Gao^* IEEE International Conference on Computer Vision (ICCV), 2021 [Paper]
	STD-Net: Structure-preserving and Topology-adaptive Deformation Network for Single-View 3D Reconstruction Aihua Mao, Canglan Dai, Qing Liu, Jie Yang, Lin Gao, Ying He and Yong-Jin Liu IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG), To Appear, 2021 [Paper]
	Variational Autoencoders for Localized Mesh Deformation Component Analysis Qingyang Tan^#, Ling-Xiao Zhang^#, Jie Yang, Yu-Kun Lai and Lin Gao^* IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2021 [Paper]
	Deep Deformation Detail Synthesis for Thin Shell Models Lan Chen, Lin Gao^, Jie Yang, Shibiao Xu^, Juntao Ye, Xiaopeng Zhang and Yu-Kun Lai CoRR abs/2102.11541 (2021) [Paper] [Video ( YouTube\|Bilibili)]
	DSG-Net: Learning Disentangled Structure and Geometry for 3D Shape Generation Jie Yang^#, Kaichun Mo^#, Yu-Kun Lai, Leonidas J. Guibas and Lin Gao ACM Transactions on Graphics, Provisional Accept with Major Revisions, 2021 [Paper] [Project] [Video ( YouTube\|Bilibili)]
	Multiscale Mesh Deformation Component Analysis with Attention-based Autoencoders Jie Yang, Lin Gao, Qingyang Tan, Yihua Huang, Shihong Xia and Yu-Kun Lai IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG), To Appear, 2021 [Paper]
	RISA-Net: Rotation-Invariant and Structure-Aware Network for Fine-grained 3D Shape Retrieval Rao Fu, Jie Yang, Jiawei Sun, Fanglue Zhang, Yu-Kun Lai and Lin Gao CoRR abs/2010.00973 (2020) [Paper] [Code]
	Learning on 3D Meshes with Laplacian Encoding and Pooling Yi-Ling Qiao, Lin Gao, Jie Yang, Paul L. Rosin, Yu-Kun Lai and Xilin Chen IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG), 2022, 28(2), 1317-1327 [Paper] [Code]
	Mesh Variational Autoencoders with Edge Contraction Pooling Yu-Jie Yuan, Yu-Kun Lai, Jie Yang, Hongbo Fu and Lin Gao CVPR 2020 WorkShop [Paper] [Code]
	SDM-NET: Deep Generative Network for Structured Deformable Mesh Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan Hongbo Fu, Yu-Kun Lai and Hao(Richard) Zhang ACM Transactions on Graphics (SIGGRAPH Asia), 38(6), 2019 [Project page] [Code] [ArXiv Preprint]
	Automatic Unpaired Shape Deformation Transfer Lin Gao, Jie Yang, Ying-Ling Qiao, Yu-Kun Lai, Paul L. Rosin, Weiwei Xu and Shihong Xia ACM Transactions on Graphics (SIGGRAPH Asia), 37(6), 2018 [Project page] [Code]
	Biharmonic deformation transfer with automatic key point selection Jie Yang, Lin Gao, Yu-Kun Lai, Paul L. Rosin and Shihong Xia Graphical Models vol. 98, 1-13,2018
	Sparse Data Driven Mesh Deformation Lin Gao, Yu-Kun Lai, Jie Yang, Ling-Xiao Zhang, Leif Kobbelt and Shihong Xia IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG), 2021, 27(3), 2085-2100 [Paper] [Code]
	Mesh-based Autoencoders for Localized Deformation Component Analysis Qingyang Tan, Lin Gao, Yu-Kun Lai, Jie Yang and Shihong Xia AAAI Conference on Artificial Intelligence (Spotlight), 2018 [Project]

Educations

University of Chinese Academy of Sciences (Computer Graphics)	September 2016 - Present
Cardiff University (Short-term Study)	November 2017 - December 2017
Sichuan University (Mathmatics)	September 2012 - July 2016

Honors and Awards

Zhuliyuehua Scholarship for Excellent Doctoral Student of Chinese Academy of Sciences	2021
Merit Student of University of Chinese Academy of Sciences	2020
4Paradigm Scholarship	2019
National Scholarship	2018
Merit Student of University of Chinese Academy of Sciences	2018
1st Prize in Academic Scholarship of University of Chinese Academy of Sciences	2017
1st Scholarship of University of Chinese Academy of Sciences	2018, 2017