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20172022
most citedEvaluation of Appearance-Based Methods and Implications for Gaze-Based Applications

114 citations · 128 across the 5 of their papers we have counts for

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cs.CV2022

Learning Video-independent Eye Contact Segmentation from In-the-Wild Videos

Tianyi Wu, Yusuke Sugano

Human eye contact is a form of non-verbal communication and can have a great influence on social behavior. Since the location and size of the eye contact targets vary across differ…

cs.CV20213 cited

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…

cs.CV20211 cited

DRIV100: In-The-Wild Multi-Domain Dataset and Evaluation for Real-World Domain Adaptation of Semantic Segmentation

Haruya Sakashita, Christoph Flothow, Noriko Takemura +1

Together with the recent advances in semantic segmentation, many domain adaptation methods have been proposed to overcome the domain gap between training and deployment environment…

cs.CV2018

Shape-conditioned Image Generation by Learning Latent Appearance Representation from Unpaired Data

Yutaro Miyauchi, Yusuke Sugano, Yasuyuki Matsushita

Conditional image generation is effective for diverse tasks including training data synthesis for learning-based computer vision. However, despite the recent advances in generative…

cs.CV201710 cited

MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation

Xucong Zhang, Yusuke Sugano, Mario Fritz +1

Learning-based methods are believed to work well for unconstrained gaze estimation, i.e. gaze estimation from a monocular RGB camera without assumptions regarding user, environment…