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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time

Published in CVPR (Oral), 2022

Liao Wang*, Jiakai Zhang*, Xinhang Liu, Fuqiang Zhao, Yanshun Zhang, Yingliang Zhang, Minye Wu, Lan Xu, Jingyi Yu

In this paper, we present a novel Fourier PlenOctree (FPO) technique to tackle efficient neural modeling and real-time rendering of dynamic scenes captured under the free-view video (FVV) setting.

| Project | Code | Paper |

NeuVV: Neural Volumetric Videos with Immersive Rendering and Editing

Published in Arxiv, 2022

Jiakai Zhang, Liao Wang, Xinhang Liu, Fuqiang Zhao, Minzhang Li, Haizhao Dai, Boyuan Zhang, Wei Yang, Lan Xu, Jingyi Yu

In this paper, we present a neural volumography technique called neural volumetric video or NeuVV to support immersive, interactive, and spatial-temporal rendering of volumetric video contents with photo-realism and in real-time.

| Paper |

Human Performance Modeling and Rendering via Neural Animated Mesh

Published in SIGGRAPH 2022 Asia, 2022

Fuqiang Zhao, Yuheng Jiang, Kaixin Yao, Jiakai Zhang, Liao Wang, Haizhao Dai, Yuhui Zhong, Yingliang Zhang, Minye Wu, Lan Xu, Jingyi Yu

To strike an intricate balance between quality and bandwidth, we propose a hierarchical solution by first rendering 6 virtual views covering the performer and then conducting occlusion-aware neural texture blending

| Project | Code | Paper |

Single-pixel p-graded-n junction spectrometers

Published in Nature Communications, 2024

Jingyi Wang, Beibei Pan, Zi Wang, Jiakai Zhang, Zhiqi Zhou, Lu Yao, Yanan Wu, Wuwei Ren, Jianyu Wang, Jingyi Yu*, Baile Chen*

We designed a novel p-graded-n junction spectrometer to measure the spectrum of materials using a neural network as a signal decoder.

| Paper |

CryoFormer: Continuous Heterogeneous Cryo-EM Reconstruction using Transformer-based Neural Representations

Published in ECCV 2024 Workshop on NFBCC (Spotlight), 2024

Xinhang Liu*, Yan Zeng*, Yifan Qin, Hao Li, Jiakai Zhang, Lan Xu, Jingyi Yu

We propose CryoFormer, a new approach for continuous heterogeneous cryo-EM reconstruction. Our approach leverages an implicit feature volume directly in the real domain as the 3D representation. We further introduce a novel query-based deformation transformer decoder to improve the reconstruction quality. Our approach is capable of refining pre-computed pose estimations and locating flexible regions.

| Project | Code | Paper |

CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy

Published in NeurIPS 2024, 2024

Jiakai Zhang*, Qihe Chen*, Yan Zeng, Wenyuan Gao, Xuming He, Zhijie Liu, and Jingyi Yu

We introduce physics-informed generative cryo-electron microscopy (CryoGEM), which for the first time integrates physics-based cryo-EM simulation with a generative unpaired noise translation to generate physically correct synthetic cryo-EM datasets with realistic noises.

| Project | Code | Paper |

talks

teaching