7 citations · 21 across the 8 of their papers we have counts for
8 papers
Fine-grained Affordance Annotation for Egocentric Hand-Object Interaction Videos
Zecheng Yu, Yifei Huang, Ryosuke Furuta +3
Object affordance is an important concept in hand-object interaction, providing information on action possibilities based on human motor capacity and objects' physical property thu…
Precise Affordance Annotation for Egocentric Action Video Datasets
Zecheng Yu, Yifei Huang, Ryosuke Furuta +3
Object affordance is an important concept in human-object interaction, providing information on action possibilities based on human motor capacity and objects' physical property th…
Efficient Annotation and Learning for 3D Hand Pose Estimation: A Survey
Takehiko Ohkawa, Ryosuke Furuta, Yoichi Sato
In this survey, we present a systematic review of 3D hand pose estimation from the perspective of efficient annotation and learning. 3D hand pose estimation has been an important r…
Background Mixup Data Augmentation for Hand and Object-in-Contact Detection
Koya Tango, Takehiko Ohkawa, Ryosuke Furuta +1
Detecting the positions of human hands and objects-in-contact (hand-object detection) in each video frame is vital for understanding human activities from videos. For training an o…
Painting Style-Aware Manga Colorization Based on Generative Adversarial Networks
Yugo Shimizu, Ryosuke Furuta, Delong Ouyang +3
Japanese comics (called manga) are traditionally created in monochrome format. In recent years, in addition to monochrome comics, full color comics, a more attractive medium, have…
PixelRL: Fully Convolutional Network with Reinforcement Learning for Image Processing
Ryosuke Furuta, Naoto Inoue, Toshihiko Yamasaki
This paper tackles a new problem setting: reinforcement learning with pixel-wise rewards (pixelRL) for image processing. After the introduction of the deep Q-network, deep RL has b…