77 citations · 123 across the 15 of their papers we have counts for
18 papers
Contrastive Losses Are Natural Criteria for Unsupervised Video Summarization
Zongshang Pang, Yuta Nakashima, Mayu Otani +1
Video summarization aims to select the most informative subset of frames in a video to facilitate efficient video browsing. Unsupervised methods usually rely on heuristic training…
Video Summarization Overview
Mayu Otani, Yale Song, Yang Wang
With the broad growth of video capturing devices and applications on the web, it is more demanding to provide desired video content for users efficiently. Video summarization facil…
Color Recommendation for Vector Graphic Documents based on Multi-Palette Representation
Qianru Qiu, Xueting Wang, Mayu Otani +1
Vector graphic documents present multiple visual elements, such as images, shapes, and texts. Choosing appropriate colors for multiple visual elements is a difficult but crucial ta…
Does Robustness on ImageNet Transfer to Downstream Tasks?
Yutaro Yamada, Mayu Otani
As clean ImageNet accuracy nears its ceiling, the research community is increasingly more concerned about robust accuracy under distributional shifts. While a variety of methods ha…
AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval
Riku Togashi, Mayu Otani, Yuta Nakashima +3
Evaluation measures have a crucial impact on the direction of research. Therefore, it is of utmost importance to develop appropriate and reliable evaluation measures for new applic…
Optimal Correction Cost for Object Detection Evaluation
Mayu Otani, Riku Togashi, Yuta Nakashima +3
Mean Average Precision (mAP) is the primary evaluation measure for object detection. Although object detection has a broad range of applications, mAP evaluates detectors in terms o…