29 citations · 57 across the 7 of their papers we have counts for
10 papers
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…
Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction
Takuma Yagi, Md Tasnimul Hasan, Yoichi Sato
Every hand-object interaction begins with contact. Despite predicting the contact state between hands and objects is useful in understanding hand-object interactions, prior methods…
EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2021: Team M3EM Technical Report
Lijin Yang, Yifei Huang, Yusuke Sugano +1
In this report, we describe the technical details of our submission to the 2021 EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition. Leveraging multip…
GO-Finder: A Registration-Free Wearable System for Assisting Users in Finding Lost Objects via Hand-Held Object Discovery
Takuma Yagi, Takumi Nishiyasu, Kunimasa Kawasaki +2
People spend an enormous amount of time and effort looking for lost objects. To help remind people of the location of lost objects, various computational systems that provide infor…
Towards Visually Explaining Video Understanding Networks with Perturbation
Zhenqiang Li, Weimin Wang, Zuoyue Li +2
''Making black box models explainable'' is a vital problem that accompanies the development of deep learning networks. For networks taking visual information as input, one basic bu…
Manipulation-skill Assessment from Videos with Spatial Attention Network
Zhenqiang Li, Yifei Huang, Minjie Cai +1
Recent advances in computer vision have made it possible to automatically assess from videos the manipulation skills of humans in performing a task, which breeds many important app…