Masataka Yamaguchi (山口正隆)

[ICCV2019] Masataka Yamaguchi et al. Subspace Structure-Aware Spectral Clustering for Robust Subspace Clustering (acceptance rate: 25%).
[BMVC2019] Masataka Yamaguchi et al. Delving Deep into Least Square Regression Model for Subspace Clustering (acceptance rate: 28%).
[WASPAA2019] Yuma Koizumi, Shoichiro Saito, Masataka Yamaguchi, Shin Murata, Noboru Harada. Batch Uniformization for Minimizing Maximum Anomaly Score of DNN-based Anomaly Detection in Sounds (acceptance rate: 43%).
[ICASSP2019] Masataka Yamaguchi, Yuma Koizumi, Noboru Harada. AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation (acceptance rate: 46%).
[ICCV2017] Masataka Yamaguchi, Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada. Spatio-temporal Person Retrieval via Natural Language Queries (acceptance rate: 29%).
[ICCV2015] Yoshitaka Ushiku, Masataka Yamaguchi, Yusuke Mukuta, Tatsuya Harada. Common Subspace for Model and Similarity: Phrase Learning for Sentence Generation from Images (acceptance rate: 30%).

[Award, ILSVRC’15] 3rd place for still image object detection with additional data in Imagenet Large Scale Visual Recognition Challenge 2015. [poster at ICCV‘15 Workshop]
- We were the closest to Deep Residual Networks (the most cited paper of the 21st century), physically.
[Invited Talk] nVidia Deep Learning Day 2016, 2016/01/15. [slide]
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