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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
EMM |
2022-03-07 15:55 |
Online |
(Primary: Online, Secondary: On-site) (Primary: Online, Secondary: On-site) |
[Poster Presentation]
Video Forgery Detection Using a Robust Hashing Algorithm Shoko Niwa, Miki Tanaka, Hitoshi Kiya (Tokyo Metro. Univ.) EMM2021-102 |
In this paper, we propose a method to detect the editing of video signals using a robust hashing algorithm. The assumed ... [more] |
EMM2021-102 pp.58-63 |
EMM |
2021-03-04 14:45 |
Online |
Online |
[Poster Presentation]
Improvement of Video Forgery Detection Using Generative Adversarial Networks Yutaro Osako (Osaka Univ.), Kazuhiro Kono (Kansai Univ.), Noboru Babaguchi (Osaka Univ.) EMM2020-72 |
Our work aims to detect tampered objects in the spatial domain of videos with high accuracy. We target videos, including... [more] |
EMM2020-72 pp.28-33 |
EMM |
2020-03-05 16:45 |
Okinawa |
(Cancelled but technical report was issued) |
[Poster Presentation]
Video Forgery Detection Using Generative Adversarial Networks Shoken Ohshiro (Osaka Univ.), Kazuhiro Kono (Kansai Univ.), Noboru Babaguchi (Osaka Univ.) EMM2019-122 |
The purpose of our work is to detect the regions of tampered objects in the spatial domain of videos by passive approach... [more] |
EMM2019-122 pp.107-112 |
EMM |
2019-03-13 15:15 |
Okinawa |
TBD |
[Poster Presentation]
A Consideration on Spatio-Temporal Feature Learning for Video Forgery Detection Shoken Ohshiro (Osaka Univ.), Kazuhiro Kono (Kansai Univ.), Noboru Babaguchi (Osaka Univ.) EMM2018-104 |
The purpose of our work is to detect objects tampered in the spatial domain of videos including dynamic scenes such as a... [more] |
EMM2018-104 pp.67-72 |
EA, ASJ-H, EMM, IPSJ-MUS [detail] |
2018-11-21 13:30 |
Ishikawa |
Hotel Koshuen |
[Poster Presentation]
Video Forgery Detection Using Spatio-Temporal Convolutional Neural Network Shoken Ohshiro (Osaka Univ), Kazuhiro Kono (Kainsai Univ), Noboru Babaguchi (Osaka Univ) EA2018-71 EMM2018-71 |
It is easy to tamper with videos due to the improvement of video editing technology.We need to develop forgery detection... [more] |
EA2018-71 EMM2018-71 pp.49-52 |
EMM |
2018-03-05 14:35 |
Kagoshima |
Naze Community Center (Amami-Shi, Kagoshima) |
[Poster Presentation]
Video Forgery Detection Considering Spatio-Temporal Consistency Takaaki Yoshida (Osaka Univ.), Kazuhiro Kono (Kansai Univ.), Noboru Babaguchi (Osaka Univ.) EMM2017-81 |
This paper proposes a video forgery detection method in dynamic scenes such as dynamic background or dynamic perspective... [more] |
EMM2017-81 pp.23-28 |
EMM |
2016-03-02 14:30 |
Kagoshima |
Yakushima Environ. and Cultural Vill. Center |
[Poster Presentation]
Video Forgery Detection Using a Time Series Model in Dynamic Scenes Shigeki Karita (Osaka Univ.), Kazuhiro Kono (Kansai Univ.), Noboru Babaguchi (Osaka Univ.) EMM2015-80 |
This paper proposes a robust video forgery detection method in dynamic scenes such as dynamic background or camera jitte... [more] |
EMM2015-80 pp.25-30 |
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