Unsupervised learning of object landmarks by factorized spatial embeddings
Learning automatically the structure of object categories remains an important open problem in computer vision. In this paper, we propose a novel unsupervised approach that can discover and learn landmarks in object categories, thus characterizing their structure. Our approach is based on factorizin...
Κύριοι συγγραφείς: | Thewlis, J, Bilen, H, Vedaldi, A |
---|---|
Μορφή: | Conference item |
Έκδοση: |
IEEE
2017
|
Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
-
Unsupervised learning of landmarks by descriptor vector exchange
ανά: Thewlis, J, κ.ά.
Έκδοση: (2020) -
Modelling and unsupervised learning of symmetric deformable object categories
ανά: Thewlis, J, κ.ά.
Έκδοση: (2018) -
Unsupervised learning of object frames by dense equivariant image labelling
ανά: Thewlis, J, κ.ά.
Έκδοση: (2017) -
Unsupervised learning of object landmarks through conditional image generation
ανά: Jakab, T, κ.ά.
Έκδοση: (2018) -
Unsupervised learning of probably symmetric deformable 3D objects from images in the wild
ανά: Wu, S, κ.ά.
Έκδοση: (2021)