no code implementations • 8 Sep 2021 • Sumin Lee, Hyunjun Eun, Jinyoung Moon, Seokeon Choi, Yoonhyung Kim, Chanho Jung, Changick Kim
To overcome this problem, we propose a novel recurrent unit, named Information Discrimination Unit (IDU), which explicitly discriminates the information relevancy between an ongoing action and others to decide whether to accumulate the input information.
no code implementations • 9 Mar 2020 • Hyunjun Eun, Daeyeong Kim, Chanho Jung, Changick Kim
Note that, instead of manual categorization requiring the heavy workload of radiologists, we propose to automatically categorize non-nodules based on the autoencoder and k-means clustering.
1 code implementation • CVPR 2020 • Hyunjun Eun, Jinyoung Moon, Jongyoul Park, Chanho Jung, Changick Kim
For online action detection, in this paper, we propose a novel recurrent unit to explicitly discriminate the information relevant to an ongoing action from others.
Ranked #13 on Online Action Detection on TVSeries
no code implementations • 26 Nov 2019 • Hyunjun Eun, Sumin Lee, Jinyoung Moon, Jongyoul Park, Chanho Jung, Changick Kim
Recent temporal action proposal generation approaches have suggested integrating segment- and snippet score-based methodologies to produce proposals with high recall and accurate boundaries.