no code implementations • 25 Sep 2023 • Katsuya Hotta, Chao Zhang, Yoshihiro Hagihara, Takuya Akashi
In this paper, we propose a novel subspace-guided feature reconstruction framework to pursue adaptive feature approximation for anomaly localization.
no code implementations • 24 Nov 2021 • Katsuya Hotta, Takuya Akashi, Shogo Tokai, Chao Zhang
Subspace clustering methods which embrace a self-expressive model that represents each data point as a linear combination of other data points in the dataset provide powerful unsupervised learning techniques.
no code implementations • 20 Jan 2020 • Chao Zhang, Xuequan Lu, Katsuya Hotta, Xi Yang
The WA data can be naturally obtained in an interactive way for specific tasks, for example, in the case of homography estimation, one can easily annotate points on the same plane/object with a single label by observing the image.