Search Results for author: Masataka Yamaguchi

Found 7 papers, 1 papers with code

Subspace Structure-Aware Spectral Clustering for Robust Subspace Clustering

no code implementations ICCV 2019 Masataka Yamaguchi, Go Irie, Takahito Kawanishi, Kunio Kashino

The most popular subspace clustering framework in recent years is the graph clustering-based approach, which performs subspace clustering in two steps: graph construction and graph clustering.

Graph Clustering graph construction

AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation

no code implementations14 Dec 2018 Masataka Yamaguchi, Yuma Koizumi, Noboru Harada

To address this difficulty, we propose AdaFlow, a new DNN-based density estimator that can be easily adapted to the change of the distribution.

Density Estimation Translation +1

Melody Generation for Pop Music via Word Representation of Musical Properties

1 code implementation31 Oct 2017 Andrew Shin, Leopold Crestel, Hiroharu Kato, Kuniaki Saito, Katsunori Ohnishi, Masataka Yamaguchi, Masahiro Nakawaki, Yoshitaka Ushiku, Tatsuya Harada

Automatic melody generation for pop music has been a long-time aspiration for both AI researchers and musicians.

Sound Multimedia Audio and Speech Processing

Spatio-temporal Person Retrieval via Natural Language Queries

no code implementations ICCV 2017 Masataka Yamaguchi, Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada

In this paper, we address the problem of spatio-temporal person retrieval from multiple videos using a natural language query, in which we output a tube (i. e., a sequence of bounding boxes) which encloses the person described by the query.

Human Detection Natural Language Queries +2

Dense Image Representation with Spatial Pyramid VLAD Coding of CNN for Locally Robust Captioning

no code implementations30 Mar 2016 Andrew Shin, Masataka Yamaguchi, Katsunori Ohnishi, Tatsuya Harada

The workflow of extracting features from images using convolutional neural networks (CNN) and generating captions with recurrent neural networks (RNN) has become a de-facto standard for image captioning task.

General Classification Image Captioning

Common Subspace for Model and Similarity: Phrase Learning for Caption Generation From Images

no code implementations ICCV 2015 Yoshitaka Ushiku, Masataka Yamaguchi, Yusuke Mukuta, Tatsuya Harada

In order to overcome the shortage of training samples, CoSMoS obtains a subspace in which (a) all feature vectors associated with the same phrase are mapped as mutually close, (b) classifiers for each phrase are learned, and (c) training samples are shared among co-occurring phrases.

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