Peizhuo Li
Peizhuo Li
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Type
Conference paper
Journal article
Date
2024
2023
2022
2021
2020
Neural Garment Dynamics via Manifold-Aware Transformers
Data driven and learning based solutions for modeling dynamic garments have significantly advanced, especially in the context of …
Peizhuo Li
,
Tuanfeng Y. Wang
,
Timur Levent Kesdogan
,
Duygu Ceylan
,
Olga Sorkine-Hornung
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Example-based Motion Synthesis via Generative Motion Matching
We present Generative Motion Matching (GenMM), a generative model that “mines” as many diverse motions as possible from a …
Weiyu Li*
,
Xuelin Chen*
,
Peizhuo Li
,
Olga Sorkine-Hornung
,
Baoquan Chen
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MoDi: Unconditional Motion Synthesis from Diverse Data
The emergence of neural networks revolutionized motion synthesis, yet synthesizing diverse motions remains challenging. We present …
Sigal Raab
,
Inbal Leibovitch
,
Peizhuo Li
,
Kfir Aberman
,
Olga Sorkine-Hornung
,
Daniel Cohen-Or
Website
Paper
Supplemental
Code
GANimator: Neural Motion Synthesis from a Single Sequence
We present GANimator, a generative model that learns to synthesize novel motions from a single, short motion sequence. GANimator …
Peizhuo Li
,
Kfir Aberman
,
Zihan Zhang
,
Rana Hanocka
,
Olga Sorkine-Hornung
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Paper
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Learning Skeletal Articulations with Neural Blend Shapes
We develop a neural technique for articulating 3D characters using enveloping with a pre-defined skeletal structure, which is essential …
Peizhuo Li
,
Kfir Aberman
,
Rana Hanocka
,
Libin Liu
,
Olga Sorkine-Hornung
,
Baoquan Chen
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Website
Paper
Supplemental
Code
Skeleton-Aware Networks for Deep Motion Retargeting
We introduce a novel deep learning framework for data-driven motion retargeting between skeletons, which may have different structure, …
Kfir Aberman*
,
Peizhuo Li*
,
Dani Lischinski
,
Olga Sorkine-Hornung
,
Daniel Cohen-Or
,
Baoquan Chen
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Paper
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