DGPose: Deep Generative Models for Human Body Analysis
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 interpretable, resulting in less flexibility. In this work, we present deep generative models for human body analysis in...
Main Authors: | de Bem, R, Ghosh, A, Ajanthan, T, Miksik, O, Boukhayma, A, Siddharth, N, Torr, P |
---|---|
Formato: | Journal article |
Publicado em: |
Springer
2020
|
Registos relacionados
-
A semi-supervised deep generative model for human body analysis
Por: De Bem, R, et al.
Publicado em: (2019) -
A conditional deep generative model of people in natural images
Por: De Bem, R, et al.
Publicado em: (2019) -
3D hand shape and pose from images in the wild
Por: Boukhayma, A, et al.
Publicado em: (2020) -
Cross-modal deep face normals with deactivable skip connections
Por: Abrevaya, VF, et al.
Publicado em: (2020) -
Variational mixture-of-experts autoencoders for multi-modal deep generative models
Por: Shi, Y, et al.
Publicado em: (2019)