1 citations · 1 across the 1 of their papers we have counts for
6 papers
Dual Mesh Convolutional Networks for Human Shape Correspondence
Nitika Verma, Adnane Boukhayma, Jakob Verbeek +1
Convolutional networks have been extremely successful for regular data structures such as 2D images and 3D voxel grids. The transposition to meshes is, however, not straight-forwar…
Cross-modal Deep Face Normals with Deactivable Skip Connections
Victoria Fernandez Abrevaya, Adnane Boukhayma, Philip H. S. Torr +1
We present an approach for estimating surface normals from in-the-wild color images of faces. While data-driven strategies have been proposed for single face images, limited availa…
Domain Partitioning Network
Botos Csaba, Adnane Boukhayma, Viveka Kulharia +2
Standard adversarial training involves two agents, namely a generator and a discriminator, playing a mini-max game. However, even if the players converge to an equilibrium, the gen…
3D Hand Shape and Pose from Images in the Wild
Adnane Boukhayma, Rodrigo de Bem, Philip H. S. Torr
We present in this work the first end-to-end deep learning based method that predicts both 3D hand shape and pose from RGB images in the wild. Our network consists of the concatena…
A Decoupled 3D Facial Shape Model by Adversarial Training
Victoria Fernandez Abrevaya, Adnane Boukhayma, Stefanie Wuhrer +1
Data-driven generative 3D face models are used to compactly encode facial shape data into meaningful parametric representations. A desirable property of these models is their abili…
DGPose: Deep Generative Models for Human Body Analysis
Rodrigo de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan +4
Deep generative modelling for human body analysis is an emerging problem with many interesting applications. However, the latent space learned by such approaches is typically not i…