151 citations · 210 across the 6 of their papers we have counts for
6 papers
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…
Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects
Ryota Yoshihashi, Tu Tuan Trinh, Rei Kawakami +3
While generic object detection has achieved large improvements with rich feature hierarchies from deep nets, detecting small objects with poor visual cues remains challenging. Moti…
Continuous 3D Label Stereo Matching using Local Expansion Moves
Tatsunori Taniai, Yasuyuki Matsushita, Yoichi Sato +1
We present an accurate stereo matching method using local expansion moves based on graph cuts. This new move-making scheme is used to efficiently infer per-pixel 3D plane labels on…