2 code implementations • 11 Apr 2024 • Minkuk Kim, Hyeon Bae Kim, Jinyoung Moon, Jinwoo Choi, Seong Tae Kim
There has been significant attention to the research on dense video captioning, which aims to automatically localize and caption all events within untrimmed video.
Ranked #3 on Dense Video Captioning on YouCook2
1 code implementation • 18 Jan 2024 • Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park
To this end, we introduce a Self-Training framework for SGG (ST-SGG) that assigns pseudo-labels for unannotated triplets based on which the SGG models are trained.
1 code implementation • 16 Oct 2023 • Kibum Kim, Kanghoon Yoon, Jaehyeong Jeon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park
Weakly-Supervised Scene Graph Generation (WSSGG) research has recently emerged as an alternative to the fully-supervised approach that heavily relies on costly annotations.
1 code implementation • 1 Dec 2022 • Kanghoon Yoon, Kibum Kim, Jinyoung Moon, Chanyoung Park
Recent scene graph generation (SGG) frameworks have focused on learning complex relationships among multiple objects in an image.
no code implementations • 28 Sep 2021 • Sunah Min, Jinyoung Moon
Consequently, the forget gate of the original LSTM can lose the accumulated information relevant to the current action because it determines which information to forget without considering the current action.
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 • 7 Sep 2021 • Jungkyoo Shin, Jinyoung Moon
Temporal moment localization aims to retrieve the best video segment matching a moment specified by a query.
1 code implementation • 25 May 2021 • Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua, Jinyoung Moon, Hong-Han Shuai
This companion paper supports the replication of the fashion trend forecasting experiments with the KERN (Knowledge Enhanced Recurrent Network) method that we presented in the ICMR 2020.
1 code implementation • 1 Dec 2020 • Youngwan Lee, Hyung-Il Kim, Kimin Yun, Jinyoung Moon
By using the proposed temporal modeling method (T-OSA), and the efficient factorized component (D(2+1)D), we construct two types of VoV3D networks, VoV3D-M and VoV3D-L.
Ranked #29 on Action Recognition on Something-Something V1 (using extra training data)
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.
no code implementations • ETRI Journal, Volume 39, Number 4, August, 2017 2017 • Jinyoung Moon, Junho Jin, Yongjin Kwon, Kyuchang Kang, Jongyoul Park, Kyoung Park
In addition, most studies have not considered extensibility for a newly added action that has been previously trained.
Ranked #1 on Action Recognition on ActionNet-VE
no code implementations • 2015 8th International Conference on Signal Processing, Image Processing and Pattern Recognition (SIP) 2015 • Jinyoung Moon, Yongjin Kwon, Kyuchang Kang, Jongyoul Park
This paper introduces a dataset for recognizing and describing interactive events between objects of interest including persons, cars, bikes, and carried objects.