8 citations · 15 across the 3 of their papers we have counts for
5 papers
Disentangled Face Identity Representations for joint 3D Face Recognition and Expression Neutralisation
Anis Kacem, Kseniya Cherenkova, Djamila Aouada
In this paper, we propose a new deep learning-based approach for disentangling face identity representations from expressive 3D faces. Given a 3D face, our approach not only extrac…
PvDeConv: Point-Voxel Deconvolution for Autoencoding CAD Construction in 3D
Kseniya Cherenkova, Djamila Aouada, Gleb Gusev
We propose a Point-Voxel DeConvolution (PVDeConv) module for 3D data autoencoder. To demonstrate its efficiency we learn to synthesize high-resolution point clouds of 10k points th…
SHARP 2020: The 1st Shape Recovery from Partial Textured 3D Scans Challenge Results
Alexandre Saint, Anis Kacem, Kseniya Cherenkova +7
The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is the first edition of a challenge fostering and benchmarking methods for recovering complete textured 3D…
3DBooSTeR: 3D Body Shape and Texture Recovery
Alexandre Saint, Anis Kacem, Kseniya Cherenkova +1
We propose 3DBooSTeR, a novel method to recover a textured 3D body mesh from a textured partial 3D scan. With the advent of virtual and augmented reality, there is a demand for cre…
A survey on Deep Learning Advances on Different 3D Data Representations
Eman Ahmed, Alexandre Saint, Abd El Rahman Shabayek +5
3D data is a valuable asset the computer vision filed as it provides rich information about the full geometry of sensed objects and scenes. Recently, with the availability of both…