Search Results for author: Asako Kanezaki

Found 11 papers, 6 papers with code

OPIRL: Sample Efficient Off-Policy Inverse Reinforcement Learning via Distribution Matching

1 code implementation9 Sep 2021 Hana Hoshino, Kei Ota, Asako Kanezaki, Rio Yokota

Inverse Reinforcement Learning (IRL) is attractive in scenarios where reward engineering can be tedious.

Training Larger Networks for Deep Reinforcement Learning

no code implementations16 Feb 2021 Kei Ota, Devesh K. Jha, Asako Kanezaki

Previous work has shown that this is mostly due to instability during training of deep RL agents when using larger networks.

Representation Learning

Deep Reactive Planning in Dynamic Environments

no code implementations31 Oct 2020 Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko SASAKI, Toshisada Mariyama, Daniel Nikovski

The main novelty of the proposed approach is that it allows a robot to learn an end-to-end policy which can adapt to changes in the environment during execution.

Path Planning using Neural A* Search

2 code implementations16 Sep 2020 Ryo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain, Mai Nishimura, Asako Kanezaki

We present Neural A*, a novel data-driven search method for path planning problems.

Unsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering

1 code implementation20 Jul 2020 Wonjik Kim, Asako Kanezaki, Masayuki Tanaka

The usage of convolutional neural networks (CNNs) for unsupervised image segmentation was investigated in this study.

Semantic Segmentation Unsupervised Image Segmentation

Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path

no code implementations3 Mar 2020 Kei Ota, Yoko SASAKI, Devesh K. Jha, Yusuke Yoshiyasu, Asako Kanezaki

Specifically, we train a deep convolutional network that can predict collision-free paths based on a map of the environment-- this is then used by a reinforcement learning algorithm to learn to closely follow the path.

Efficient Exploration

Salient object detection on hyperspectral images using features learned from unsupervised segmentation task

1 code implementation28 Feb 2019 Nevrez Imamoglu, Guanqun Ding, Yuming Fang, Asako Kanezaki, Toru Kouyama, Ryosuke Nakamura

Various saliency detection algorithms from color images have been proposed to mimic eye fixation or attentive object detection response of human observers for the same scenes.

RGB Salient Object Detection Saliency Detection +3

RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints

1 code implementation CVPR 2018 Asako Kanezaki, Yasuyuki Matsushita, Yoshifumi Nishida

We propose a Convolutional Neural Network (CNN)-based model "RotationNet," which takes multi-view images of an object as input and jointly estimates its pose and object category.

3D Object Classification Object Classification +1

Recognizing Activities of Daily Living with a Wrist-mounted Camera

no code implementations CVPR 2016 Katsunori Ohnishi, Atsushi Kanehira, Asako Kanezaki, Tatsuya Harada

We present a novel dataset and a novel algorithm for recognizing activities of daily living (ADL) from a first-person wearable camera.

Object Detection

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