Vibro: Video Browsing with Semantic and Visual Image Embeddings

被引：6

作者：

Schall, Konstantin ^{[1
]}

Hezel, Nico ^{[1
]}

Jung, Klaus ^{[1
]}

Barthel, Kai Uwe ^{[1
]}

机构：

[1] Univ Appl Sci, HTW Berlin, Visual Comp Grp, Wilhelminenhofstr 75, D-12459 Berlin, Germany

来源：

MULTIMEDIA MODELING, MMM 2023, PT I | 2023年 / 13833卷

关键词：

Content-based video retrieval; Exploration; Visualization; Image browsing; Visual and textual co-embeddings;

D O I：

10.1007/978-3-031-27077-2_56

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Vibro represents a powerful tool for interactive video retrieval and browsing and is the winner of the Video Browser Showdown 2022. Following the saying of "never change a winning system" we did not change any of the underlying concepts nor added any new features. Instead, we focused on improving the three existing cornerstones of the software, which are text-to-image search, image-to-image search and browsing results with 2D sorted maps. The changes to these three parts are summarized in this paper, and in addition, an overview of the AVS-mode of vibro is given.

引用

页码：665 / 670

页数：6

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