Published in NeurIPS 2024, 2024
Yingjun Shen*, Haizhao Dai*, Qihe Chen, Yan Zeng, Jiakai Zhang, Yuan Pei, Jingyi Yu
We introduce DRACO, a Denoising-Reconstruction Autoencoder for CryO-EM, inspired by the Noise2Noise (N2N) approach.
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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.
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.
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.
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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
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.
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Published in CVPR, 2022
Fuqiang Zhao, Wei Yang, Jiakai Zhang, Pei Lin, Yingliang Zhang, Jingyi Yu, Lan Xu
We present HumanNeRF - a generalizable neural representation - for high-fidelity free-view synthesis of dynamic humans.
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.
Published in SIGGRAPH, 2021
Jiakai Zhang, Xinhang Liu, Xinyi Ye, Fuqiang Zhao, Yanshun Zhang, Minye Wu, Yingliang Zhang, Lan Xu and Jingyi Yu
In this paper we propose the first approach for editable photo-realistic free-viewpoint video generation for large-scale dynamic scenes using only sparse 16 cameras.
| Project | Code | Paper | Two Minute Papers | Interview with German National Audio
Published in ACM MM, 2020
Quan Meng, Jiakai Zhang, Qiang Hu, Xuming He, Jingyi Yu
We present a novel real-time line segment detection scheme called Line Graph Neural Network (LGNN).
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