CEAT: Curvature Feature Extractor Using Action Based Triplet Learning for Action Segmentation

CEAT: Curvature Feature Extractor Using Action Based Triplet Learning for Action Segmentation

With the continued growth of untrimmed videos on the internet, there is an increasing demand for advanced action segmentation methods, capable of accurately and semantically localizing sequences within lengthy videos. Traditional approaches have attempted to overcome the prevalent issue of over-segm...

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Detaylı Bibliyografya
Asıl Yazarlar: Seungmin Jang, Jeong-Hyeon Moon, So Yeon Kim, Kyung-Ah Sohn
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: IEEE 2023-01-01
Seri Bilgileri:IEEE Access
Konular:
Action segmentation
Bezier curve approximation
contrastive learning
Online Erişim:https://ieeexplore.ieee.org/document/10194929/

Internet

https://ieeexplore.ieee.org/document/10194929/

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