7 citations · 23 across the 5 of their papers we have counts for
5 papers
Batch Uniformization for Minimizing Maximum Anomaly Score of DNN-based Anomaly Detection in Sounds
Yuma Koizumi, Shoichiro Saito, Masataka Yamaguchi +2
Use of an autoencoder (AE) as a normal model is a state-of-the-art technique for unsupervised-anomaly detection in sounds (ADS). The AE is trained to minimize the sample mean of th…
AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation
Masataka Yamaguchi, Yuma Koizumi, Noboru Harada
We tackle unsupervised anomaly detection (UAD), a problem of detecting data that significantly differ from normal data. UAD is typically solved by using density estimation. Recentl…
Melody Generation for Pop Music via Word Representation of Musical Properties
Andrew Shin, Leopold Crestel, Hiroharu Kato +6
Automatic melody generation for pop music has been a long-time aspiration for both AI researchers and musicians. However, learning to generate euphonious melody has turned out to b…
Spatio-temporal Person Retrieval via Natural Language Queries
Masataka Yamaguchi, Kuniaki Saito, Yoshitaka Ushiku +1
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 boundi…
Dense Image Representation with Spatial Pyramid VLAD Coding of CNN for Locally Robust Captioning
Andrew Shin, Masataka Yamaguchi, Katsunori Ohnishi +1
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 standar…