Zobrazeno 1 - 9
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pro vyhledávání: '"Desnica, Zoranka"'
We propose a new model-based algorithm solving the inverse rig problem in facial animation retargeting, exhibiting higher accuracy of the fit and sparser, more interpretable weight vector compared to SOTA. The proposed method targets a specific subdo
Externí odkaz:
http://arxiv.org/abs/2302.04843
We propose a method to fit arbitrarily accurate blendshape rig models by solving the inverse rig problem in realistic human face animation. The method considers blendshape models with different levels of added corrections and solves the regularized l
Externí odkaz:
http://arxiv.org/abs/2302.04820
Automated methods for facial animation are a necessary tool in the modern industry since the standard blendshape head models consist of hundreds of controllers and a manual approach is painfully slow. Different solutions have been proposed that produ
Externí odkaz:
http://arxiv.org/abs/2205.04289
Estimations and evaluations of the main patterns of time series data in groups benefit large amounts of applications in various fields. Different from the classical auto-correlation time series analysis and the modern neural networks techniques, in t
Externí odkaz:
http://arxiv.org/abs/2203.14251
Digital human animation relies on high-quality 3D models of the human face -- rigs. A face rig must be accurate and, at the same time, fast to compute. One of the most common rigging models is the blendshape model. We present a novel approach for lea
Externí odkaz:
http://arxiv.org/abs/2110.15313
Digital human animation relies on high-quality 3D models of the human face: rigs. A face rig must be accurate and, at the same time, fast to compute. One of the most common rigging models is the blendshape model. We propose a novel algorithm for solv
Externí odkaz:
http://arxiv.org/abs/2109.08356
There is an increasing scientific interest in automatically analysing and understanding human behavior, with particular reference to the evolution of facial expressions and the recognition of the corresponding emotions. In this paper we propose a tec
Externí odkaz:
http://arxiv.org/abs/2103.00844
Publikováno v:
Optimization Letters; Mar2024, Vol. 18 Issue 2, p545-559, 15p
Akademický článek
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