108 citations · 153 across the 10 of their papers we have counts for
12 papers
Edge-Level Explanations for Graph Neural Networks by Extending Explainability Methods for Convolutional Neural Networks
Tetsu Kasanishi, Xueting Wang, Toshihiko Yamasaki
Graph Neural Networks (GNNs) are deep learning models that take graph data as inputs, and they are applied to various tasks such as traffic prediction and molecular property predic…
Predicting Online Video Advertising Effects with Multimodal Deep Learning
Jun Ikeda, Hiroyuki Seshime, Xueting Wang +1
With expansion of the video advertising market, research to predict the effects of video advertising is getting more attention. Although effect prediction of image advertising has…
Self-Play Reinforcement Learning for Fast Image Retargeting
Nobukatsu Kajiura, Satoshi Kosugi, Xueting Wang +1
In this study, we address image retargeting, which is a task that adjusts input images to arbitrary sizes. In one of the best-performing methods called MULTIOP, multiple retargetin…
Pretext-Contrastive Learning: Toward Good Practices in Self-supervised Video Representation Leaning
Li Tao, Xueting Wang, Toshihiko Yamasaki
Recently, pretext-task based methods are proposed one after another in self-supervised video feature learning. Meanwhile, contrastive learning methods also yield good performance.…
Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework
Li Tao, Xueting Wang, Toshihiko Yamasaki
We propose a self-supervised method to learn feature representations from videos. A standard approach in traditional self-supervised methods uses positive-negative data pairs to tr…
Image Aesthetics Prediction Using Multiple Patches Preserving the Original Aspect Ratio of Contents
Lijie Wang, Xueting Wang, Toshihiko Yamasaki
The spread of social networking services has created an increasing demand for selecting, editing, and generating impressive images. This trend increases the importance of evaluatin…