17 citations · 90 across the 19 of their papers we have counts for
29 papers
Improved Few-shot Segmentation by Redefinition of the Roles of Multi-level CNN Features
Zhijie Wang, Masanori Suganuma, Takayuki Okatani
This study is concerned with few-shot segmentation, i.e., segmenting the region of an unseen object class in a query image, given support image(s) of its instances. The current met…
Matching in the Dark: A Dataset for Matching Image Pairs of Low-light Scenes
Wenzheng Song, Masanori Suganuma, Xing Liu +3
This paper considers matching images of low-light scenes, aiming to widen the frontier of SfM and visual SLAM applications. Recent image sensors can record the brightness of scenes…
Progressive and Selective Fusion Network for High Dynamic Range Imaging
Qian Ye, Jun Xiao, Kin-man Lam +1
This paper considers the problem of generating an HDR image of a scene from its LDR images. Recent studies employ deep learning and solve the problem in an end-to-end fashion, lead…
Pushing the Envelope of Thin Crack Detection
Liang Xu, Taro Hatsutani, Xing Liu +3
In this study, we consider the problem of detecting cracks from the image of a concrete surface for automated inspection of infrastructure, such as bridges. Its overall accuracy is…
Bridging In- and Out-of-distribution Samples for Their Better Discriminability
Engkarat Techapanurak, Anh-Chuong Dang, Takayuki Okatani
This paper proposes a method for OOD detection. Questioning the premise of previous studies that ID and OOD samples are separated distinctly, we consider samples lying in the inter…
Practical Evaluation of Out-of-Distribution Detection Methods for Image Classification
Engkarat Techapanurak, Takayuki Okatani
We reconsider the evaluation of OOD detection methods for image recognition. Although many studies have been conducted so far to build better OOD detection methods, most of them fo…