Zobrazeno 1 - 10
of 402
pro vyhledávání: '"DAOUDI, Mohamed"'
Autor:
Nocentini, Federico, Besnier, Thomas, Ferrari, Claudio, Arguillere, Sylvain, Berretti, Stefano, Daoudi, Mohamed
Generating speech-driven 3D talking heads presents numerous challenges; among those is dealing with varying mesh topologies. Existing methods require a registered setting, where all meshes share a common topology: a point-wise correspondence across a
Externí odkaz:
http://arxiv.org/abs/2410.11041
Content and image generation consist in creating or generating data from noisy information by extracting specific features such as texture, edges, and other thin image structures. We are interested here in generative models, and two main problems are
Externí odkaz:
http://arxiv.org/abs/2403.14897
Autor:
Nocentini, Federico, Besnier, Thomas, Ferrari, Claudio, Arguillere, Sylvain, Berretti, Stefano, Daoudi, Mohamed
Speech-driven 3D talking heads generation has emerged as a significant area of interest among researchers, presenting numerous challenges. Existing methods are constrained by animating faces with fixed topologies, wherein point-wise correspondence is
Externí odkaz:
http://arxiv.org/abs/2403.10942
This paper introduces a new mathematical and numerical framework for surface analysis derived from the general setting of elastic Riemannian metrics on shape spaces. Traditionally, those metrics are defined over the infinite dimensional manifold of i
Externí odkaz:
http://arxiv.org/abs/2311.04382
3D generative modeling is accelerating as the technology allowing the capture of geometric data is developing. However, the acquired data is often inconsistent, resulting in unregistered meshes or point clouds. Many generative learning algorithms req
Externí odkaz:
http://arxiv.org/abs/2306.15762
Recently, wearable emotion recognition based on peripheral physiological signals has drawn massive attention due to its less invasive nature and its applicability in real-life scenarios. However, how to effectively fuse multimodal data remains a chal
Externí odkaz:
http://arxiv.org/abs/2303.17611
The generation of natural human motion interactions is a hot topic in computer vision and computer animation. It is a challenging task due to the diversity of possible human motion interactions. Diffusion models, which have already shown remarkable g
Externí odkaz:
http://arxiv.org/abs/2301.10134
We present Basis Restricted Elastic Shape Analysis (BaRe-ESA), a novel Riemannian framework for human body scan representation, interpolation and extrapolation. BaRe-ESA operates directly on unregistered meshes, i.e., without the need to establish pr
Externí odkaz:
http://arxiv.org/abs/2211.13185
Autor:
Szczapa, Benjamin, Daoudi, Mohamed, Berretti, Stefano, Pala, Pietro, Del Bimbo, Alberto, Hammal, Zakia
We propose an automatic method to estimate self-reported pain based on facial landmarks extracted from videos. For each video sequence, we decompose the face into four different regions and the pain intensity is measured by modeling the dynamics of f
Externí odkaz:
http://arxiv.org/abs/2209.01813