178 citations · 214 across the 4 of their papers we have counts for
5 papers
Multi-Object Tracking as Attention Mechanism
Hiroshi Fukui, Taiki Miyagawa, Yusuke Morishita
We propose a conceptually simple and thus fast multi-object tracking (MOT) model that does not require any attached modules, such as the Kalman filter, Hungarian algorithm, transfo…
Visual Explanation of Deep Q-Network for Robot Navigation by Fine-tuning Attention Branch
Yuya Maruyama, Hiroshi Fukui, Tsubasa Hirakawa +3
Robot navigation with deep reinforcement learning (RL) achieves higher performance and performs well under complex environment. Meanwhile, the interpretation of the decision-making…
Embedding Human Knowledge into Deep Neural Network via Attention Map
Masahiro Mitsuhara, Hiroshi Fukui, Yusuke Sakashita +4
In this work, we aim to realize a method for embedding human knowledge into deep neural networks. While the conventional method to embed human knowledge has been applied for non-de…
Attention Branch Network: Learning of Attention Mechanism for Visual Explanation
Hiroshi Fukui, Tsubasa Hirakawa, Takayoshi Yamashita +1
Visual explanation enables human to understand the decision making of Deep Convolutional Neural Network (CNN), but it is insufficient to contribute the performance improvement. In…
Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets
Kenji Enomoto, Ken Sakurada, Weimin Wang +4
In this paper, we propose a method for cloud removal from visible light RGB satellite images by extending the conditional Generative Adversarial Networks (cGANs) from RGB images to…