18 citations · 21 across the 4 of their papers we have counts for
7 papers
Parameter Efficient Transfer Learning for Various Speech Processing Tasks
Shinta Otake, Rei Kawakami, Nakamasa Inoue
Fine-tuning of self-supervised models is a powerful transfer learning method in a variety of fields, including speech processing, since it can utilize generic feature representatio…
Informative Sample-Aware Proxy for Deep Metric Learning
Aoyu Li, Ikuro Sato, Kohta Ishikawa +2
Among various supervised deep metric learning methods proxy-based approaches have achieved high retrieval accuracies. Proxies, which are class-representative points in an embedding…
Finding a Needle in a Haystack: Tiny Flying Object Detection in 4K Videos using a Joint Detection-and-Tracking Approach
Ryota Yoshihashi, Rei Kawakami, Shaodi You +3
Detecting tiny objects in a high-resolution video is challenging because the visual information is little and unreliable. Specifically, the challenge includes very low resolution o…
Hybrid Loss for Learning Single-Image-based HDR Reconstruction
Kenta Moriwaki, Ryota Yoshihashi, Rei Kawakami +2
This paper tackles high-dynamic-range (HDR) image reconstruction given only a single low-dynamic-range (LDR) image as input. While the existing methods focus on minimizing the mean…
Classification-Reconstruction Learning for Open-Set Recognition
Ryota Yoshihashi, Wen Shao, Rei Kawakami +3
Open-set classification is a problem of handling `unknown' classes that are not contained in the training dataset, whereas traditional classifiers assume that only known classes ap…
Cross-connected Networks for Multi-task Learning of Detection and Segmentation
Seiichiro Fukuda, Ryota Yoshihashi, Rei Kawakami +3
Multi-task learning improves generalization performance by sharing knowledge among related tasks. Existing models are for task combinations annotated on the same dataset, while the…