Large-scale learning of discriminative image representations
<p>This thesis addresses the problem of designing discriminative image representations for a variety of computer vision tasks. Our approach is to employ large-scale machine learning to obtain novel representations and improve the existing ones. This allows us to propose descriptors for a va...
Main Author: | Simonyan, K |
---|---|
Other Authors: | Zisserman, A |
Format: | Thesis |
Language: | English |
Published: |
2013
|
Subjects: |
Similar Items
-
Self-supervised learning of structural representations of visual objects
by: Jakab, T
Published: (2021) -
Self-supervised video representation learning
by: Han, T
Published: (2022) -
Representation of spatial transformations in deep neural networks
by: Lenc, K
Published: (2017) -
Algorithms for image saliency via sparse representation and multi-scale inputs image retargeting
by: Hoang, Minh Chau
Published: (2012) -
Learning to understand large-scale 3D point clouds
by: Qingyong, H
Published: (2022)