Zhiqin Chen

Research Scientist, Adobe Research, Seattle

zchen@adobe.com          Google Scholar          GitHub

I am a research scientist at Adobe based in Seattle. I received my PhD and Master's degree from Simon Fraser University, supervised by Prof. Hao (Richard) Zhang, and obtained my Bachelor's degree from Shanghai Jiao Tong University. I have won the best student paper award at CVPR 2020 and best paper award candidate at CVPR 2023. I was an NVIDIA graduate fellowship finalist and received Google PhD Fellowship in 2021. I have also won Alain Fournier Dissertation Award and Eurographics PhD Thesis Award in 2024. My research interest is in computer graphics with a specialty in geometric modeling, machine learning, 3D reconstruction, and shape synthesis.


Publications

2024

Controllable Shape Modeling with Neural Generalized Cylinder
Xiangyu Zhu, Zhiqin Chen, Ruizhen Hu, Xiaoguang Han
SIGGRAPH Asia 2024 (conference)
[ArXiv]
Text-guided Controllable Mesh Refinement for Interactive 3D Modeling
Yun-Chun Chen, Selena Ling, Zhiqin Chen, Vladimir G. Kim, Matheus Gadelha, Alec Jacobson
SIGGRAPH Asia 2024 (conference)
[ArXiv]
DECOLLAGE: 3D Detailization by Controllable, Localized, and Learned Geometry Enhancement
Qimin Chen, Zhiqin Chen, Vladimir G. Kim, Noam Aigerman, Hao Zhang, Siddhartha Chaudhuri
ECCV 2024
[ArXiv] [Project page] [GitHub]
DAE-Net: Deforming Auto-Encoder for fine-grained shape co-segmentation
Zhiqin Chen, Qimin Chen, Hang Zhou, Hao Zhang
SIGGRAPH 2024 (conference)
[ArXiv] [GitHub]

2023

ShaDDR: Real-Time Example-Based Geometry and Texture Generation via 3D Shape Detailization and Differentiable Rendering
Qimin Chen, Zhiqin Chen, Hang Zhou, Hao Zhang
SIGGRAPH Asia 2023 (conference)
[ArXiv] [GitHub]
Neural Mesh Reconstruction
Zhiqin Chen
PhD thesis, Simon Fraser University, 2023
[PDF]
A Review of Deep Learning-Powered Mesh Reconstruction Methods
Zhiqin Chen
PhD depth report
[ArXiv]
MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures
Zhiqin Chen, Thomas Funkhouser, Peter Hedman, Andrea Tagliasacchi
CVPR 2023 Best Paper Award Candidate
[ArXiv] [GitHub] [Project page] [Video]

2022

Neural Dual Contouring
Zhiqin Chen, Andrea Tagliasacchi, Thomas Funkhouser, Hao Zhang
SIGGRAPH 2022 (journal)
[ArXiv] [GitHub] [Video]
AUV-Net: Learning Aligned UV Maps for Texture Transfer and Synthesis
Zhiqin Chen, Kangxue Yin, Sanja Fidler
CVPR 2022
[ArXiv] [Project page] [Video]
CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assembly
Fenggen Yu, Zhiqin Chen, Manyi Li, Aditya Sanghi, Hooman Shayani, Ali Mahdavi-Amiri, Hao Zhang
CVPR 2022
[ArXiv] [GitHub] [Project page] [Video]

2021

Neural Marching Cubes
Zhiqin Chen, Hao Zhang
SIGGRAPH Asia 2021 (journal)
[ArXiv] [GitHub] [Video]
DECOR-GAN: 3D Shape Detailization by Conditional Refinement
Zhiqin Chen, Vladimir G. Kim, Matthew Fisher, Noam Aigerman, Hao Zhang, Siddhartha Chaudhuri
CVPR 2021 (oral)
[ArXiv] [GitHub] [Video] [GUI demo]
Learning Mesh Representations via Binary Space Partitioning Tree Networks
Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
[ArXiv] [GitHub]

2020

COALESCE: Component Assembly by Learning to Synthesize Connections
Kangxue Yin, Zhiqin Chen, Siddhartha Chaudhuri, Matthew Fisher, Vladimir G. Kim, Hao Zhang
3DV 2020 (oral)
[ArXiv] [GitHub] [Video]
BSP-Net: Generating Compact Meshes via Binary Space Partitioning
Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang
CVPR 2020 Best Student Paper Award
[ArXiv] [GitHub] [Video] [Project page]

2019

LOGAN: Unpaired Shape Transform in Latent Overcomplete Space
Kangxue Yin, Zhiqin Chen, Hui Huang, Daniel Cohen-Or, Hao Zhang
SIGGRAPH Asia 2019
[ArXiv] [GitHub]
BAE-NET: Branched Autoencoder for Shape Co-Segmentation
Zhiqin Chen, Kangxue Yin, Matthew Fisher, Siddhartha Chaudhuri, Hao Zhang
ICCV 2019
[ArXiv] [GitHub]
Learning Implicit Fields for Generative Shape Modeling
Zhiqin Chen, Hao Zhang
CVPR 2019
[ArXiv] [GitHub]
BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image Synthesis
Zili Yi, Zhiqin Chen, Hao Cai, Wendong Mao, Minglun Gong, Hao Zhang
IEEE Transactions on Image Processing (TIP)
[ArXiv] [GitHub]


Awards and honors

Presenting Project Turntable at Adobe MAX Sneaks, 2024
Governor General’s Gold Convocation Medal, 2024
Alain Fournier Dissertation Award, 2024
Eurographics PhD Thesis Award, 2024
Best Paper Award Candidate, CVPR 2023
Google PhD Fellowship, 2021,2022
NVIDIA Graduate Fellowship Finalist, 2021
Best Student Paper Award, CVPR 2020


Working experience

Adobe Internship, May - Nov, 2020
NVIDIA Internship, May - Nov, 2021
Google Student Researcher, Nov 2021 - Jul 2022
Adobe Research Scientist, Aug 2023 - Now


Reviewer

SIGGRAPH 2022, 2023, 2024
SIGGRAPH Asia 2020, 2022, 2023, 2024
TOG 2020, 2023
CVPR 2020, 2021, 2022, 2023, 2024
ICCV 2021, 2023
IJCAI 2021, 2022, 2023
WACV 2021
IJCV 2021
3DV 2021
TVCG 2021, 2022
EG 2022, 2024
PG 2019, 2020
TIP 2022
NeurIPS 2023
TPAMI 2024