Muyao Niu
Hi, I'm Muyao Niu.
I am a 2nd year master student in the Department of Mechano-Informatics, the University of Tokyo (UTokyo). My supervisor is Prof. Yinqiang Zheng . I received my B.E. degree from Dalian University of Technology in 2022. My research interests include Computational Photography, AIGC, and 3D Vision.
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WeChat: MyNiuuu
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MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Model
Muyao Niu,
Xiaodong Cun,
Xintao Wang,
Yong Zhang,
Ying Shan,
Yinqiang Zheng
ECCV, 2024
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We introduce MOFA-Video to adapt motions from different domains to the frozen Video Diffusion Model. MOFA-Video can effectively animate a single image using various types of control signals, including trajectories, keypoint sequences, and their combinations.
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CV-VAE: A Compatible Video VAE for Latent Generative Video Models
Sijie Zhao,
Yong Zhang,
Xiaodong Cun,
Shaoshu Yang,
Muyao Niu,
Xiaoyu Li,
Wenbo Hu,
Ying Shan
arXiv, 2024
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We propose CV-VAE that is compatible with existing image and video models trained with SD image VAE. Our video VAE provides a truly spatio-temporally compressed latent space for latent generative video models, as opposed to uniform frame sampling.
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Physics-Based Adversarial Attack on Near-Infrared Human Detector for Nighttime Surveillance Camera Systems
Muyao Niu,
Zhuoxiao Li
Yifan Zhan,
Huy H. Nguyen,
Isao Echizen,
Yinqiang Zheng
ACM MM, 2023
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We introduced an innovative approach that passively manipulates the intensity distribution of NIR images and developed a 3D-aware, black-box attack algorithm to target deep learning-based NIR-powered human detection systems.
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NIR-assisted Video Enhancement via Unpaired 24-hour Data
Muyao Niu,
Zhihang Zhong,
Yinqiang Zheng
ICCV, 2023
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We addressed the issue of collecting data for utilizing NIR images to improve low-light VIS videos. Physiscs-inspired algorithms are designed to simulate pseudo paired data of NIR and VIS images, simulating day-to-night situations. We then trained an enhancement network using the generated pseudo data.
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Visibility Constrained Wide-band Illumination Spectrum Design for Seeing-in-the-Dark
Muyao Niu,
Zhuoxiao Li,
Zhihang Zhong,
Yinqiang Zheng
CVPR, 2023
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We designed an optimal illumination spectrum in the VIS-NIR range by considering human vision constraints, which significantly improves translation performance. A fully differentiable model was proposed, which includes the imaging process, human visual perception, and the enhancement network.
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Region Assisted Sketch Colorization
Ning Wang*,
Muyao Niu*,
Zhihui Wang,
Kun Hu,
Bin Liu,
Zhiyong Wang,
Haojie Li
TIP, 2023
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we proposed the Region-Assisted Sketch Colorization (RASC) method, which uses a 'Region Map' to better utilize regional information within the sketch, enhancing the perception of region-wise features.
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Interns
2023.12 - Now: Computer Vision Research Intern at Computer Vision Center, Tencent AI Lab, mentored by Xiaodong Cun.
2021.08 - 2022.01: Computer Vision Research Intern at SenseVideo Group, SenseTime Research, mentored by Siwei Tang.
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Awards/Scholarships
WING-CFS Special Research Assistant Scholarship, The University of Tokyo, 2023.04 - 2027.09
Teijin Scholarship, 2023.04 - 2024.09
JASSO Scholarship, 2022.10 - 2023.04
National Scholarship of China (Undergraduate Students), 2019.09 - 2021.08
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The template comes from the personal website of Jon Barron.
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