A conditional deep generative model of people in natural images
We propose a deep generative model of humans in natural images which keeps 2D pose separated from other latent factors of variation, such as background scene and clothing. In contrast to methods that learn generative models of low-dimensional representations, e.g., segmentation masks and 2D skeleton...
Κύριοι συγγραφείς: | De Bem, R, Ghosh, A, Boukhayma, A, Ajanthan, T, Siddharth, N, Torr, P |
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Μορφή: | Conference item |
Έκδοση: |
IEEE
2019
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Παρόμοια τεκμήρια
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DGPose: Deep Generative Models for Human Body Analysis
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Έκδοση: (2020) -
A semi-supervised deep generative model for human body analysis
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Έκδοση: (2019) -
3D hand shape and pose from images in the wild
ανά: Boukhayma, A, κ.ά.
Έκδοση: (2020) -
Looking deep at people: towards understanding and generating humans in images with deep learning
ανά: de Bem, RA
Έκδοση: (2018) -
Cross-modal deep face normals with deactivable skip connections
ανά: Abrevaya, VF, κ.ά.
Έκδοση: (2020)