125 citations · 206 across the 6 of their papers we have counts for
3 papers · 1 filter
Improving Bi-directional Generation between Different Modalities with Variational Autoencoders
Masahiro Suzuki, Kotaro Nakayama, Yutaka Matsuo
We investigate deep generative models that can exchange multiple modalities bi-directionally, e.g., generating images from corresponding texts and vice versa. A major approach to a…
Generative Adversarial Nets from a Density Ratio Estimation Perspective
Masatoshi Uehara, Issei Sato, Masahiro Suzuki +2
Generative adversarial networks (GANs) are successful deep generative models. GANs are based on a two-player minimax game. However, the objective function derived in the original m…
Joint Multimodal Learning with Deep Generative Models
Masahiro Suzuki, Kotaro Nakayama, Yutaka Matsuo
We investigate deep generative models that can exchange multiple modalities bi-directionally, e.g., generating images from corresponding texts and vice versa. Recently, some studie…