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I am a 3rd-year PhD student in School of Computer Science at Fudan University, supervised by Prof. Bo Yan. Before that, I received my Bachelor's degree of Computer Science at Fudan University in 2021. My research interests lie in the field of video synthesis, low-level vision and postprocessing of rendering. Email: rahe16 (at) fudan.edu.cn. CV / Google Scholar / Semantic Scholar / DBLP / Github / Zhihu / Bilibili |
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(*: Equal contribution) |
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Chenxi Ma*, Weimin Tan*, Ruian He, Bo Yan Nature Methods, 2024 We provide a universal fluorescence microscopy-based image restoration (UniFMIR) model to address different restoration problems, and show that UniFMIR offers higher image restoration precision, better generalization and increased versatility. |
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Ruian He*, Shili Zhou*, Yuqi Sun, Ri Cheng, Weimin Tan , Bo Yan AAAI, 2024 We recognize the shared context and mechanisms between frame supersampling and extrapolation, save up to 75% of time against the conventional two-stage pipeline that necessitates 17ms. |
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Shili Zhou, Ruian He, Weimin Tan , Bo Yan AAAI, 2024 Through theoretical analysis, we find the pre-trained large vision models are helpful in optical flow estimation, and SAM is suitable for solving the fragmentation problem. |
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Ri Cheng, Ruian He, Xuhao Jiang, Shili Zhou, Weimin Tan , Bo Yan AAAI, 2024 We develop a Context-Aware Iteration Policy Network, which determines the optimal number of iterations per sample and reduce FLOPs by about 40%/20% for the Sintel/KITTI datasets. |
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Ri Cheng , Xuhao Jiang , Ruian He, Shili Zhou , Weimin Tan , Bo Yan ACMMM, 2023 We develop an Uncertainty-Guided Spatial Pruning (UGSP) architecture to skip redundant computation for efficient frame interpolation dynamically. |
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Shili Zhou*, Xuhao Jiang*, Weimin Tan, Ruian He, Bo Yan ACMMM, 2023 We propose an optical flow model, MVFlow, which uses motion vectors to improve the speed and accuracy of optical flow estimation for compressed videos. |
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Ruian He, Shili Zhou, Ri Cheng, Yuqi Sun, Weimin Tan, Bo Yan The 3nd Anti-UAV Workshop & Challenge - CVPR Workshops, 2023 Our method utilizes the frame difference of multiple previous frames and fuse multiple spatial-temporal scales. |
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Yu Bai, Ruian He, Weimin Tan, Bo Yan, Yangle Lin ICASSP, 2023 We propose a novel fine-grained blind face inpainting framework and build up a new dataset called CelebO-3D. |
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Zhen Xing*, Weimin Tan*, Ruian He, Yangle Lin, Bo Yan ACMMM, 2022 We propose a task-specific framework which first combines occlusion discarding and feature completion together to reduce the interference of occlusions on instance level. |
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Conference Reviewer / Program Committee Member for AAAI (2023, 2024), CVPR (2022, 2024), ICCV (2023), ECCV (2024), IEEEVR (2023), ACMMM (2024). Journal Reviewer for TCSVT (2024). |
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Updated at April 2024.
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