2 citations · 3 across the 20 of their papers we have counts for
4 papers · 1 filter
Feature-Based Lie Group Transformer for Real-World Applications
Takayuki Komatsu, Yoshiyuki Ohmura, Kayato Nishitsunoi +1
The main goal of representation learning is to acquire meaningful representations from real-world sensory inputs without supervision. Representation learning explains some aspects…
Learning Conditionally Independent Transformations using Normal Subgroups in Group Theory
Kayato Nishitsunoi, Yoshiyuki Ohmura, Takayuki Komatsu +1
Humans develop certain cognitive abilities to recognize objects and their transformations without explicit supervision, highlighting the importance of unsupervised representation l…
Ablation Study to Clarify the Mechanism of Object Segmentation in Multi-Object Representation Learning
Takayuki Komatsu, Yoshiyuki Ohmura, Yasuo Kuniyoshi
Multi-object representation learning aims to represent complex real-world visual input using the composition of multiple objects. Representation learning methods have often used un…
Disentangling Patterns and Transformations from One Sequence of Images with Shape-invariant Lie Group Transformer
T. Takada, W. Shimaya, Y. Ohmura +1
An effective way to model the complex real world is to view the world as a composition of basic components of objects and transformations. Although humans through development under…