2017 IEEE International Conference on Computer Vision Workshops (ICCVW) 2017
DOI: 10.1109/iccvw.2017.49
|View full text |Cite
|
Sign up to set email alerts
|

Near-Duplicate Video Retrieval with Deep Metric Learning

Abstract: This work addresses the problem of Near-Duplicate Video Retrieval (NDVR). We propose an effective videolevel NDVR scheme based on deep metric learning that leverages Convolutional Neural Network (CNN) features from intermediate layers to generate discriminative global video representations in tandem with a Deep Metric Learning (DML) framework with two fusion variations, trained to approximate an embedding function for accurate distance calculation between two near-duplicate videos. In contrast to most state-of… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
64
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
5

Relationship

2
3

Authors

Journals

citations
Cited by 71 publications
(64 citation statements)
references
References 29 publications
0
64
0
Order By: Relevance
“…• The video title, event title, and the four translations are submitted as search queries to the three target platforms (YouTube, Facebook, Twitter) and all results are aggregated in a common pool. • Using the near-duplicate retrieval algorithm of Kordopatis-Zilos et al [27], we filter the pool of videos in order to discard unrelated ones. • Finally a manual confirmation step is used to remove erroneous results of the automatic method and only retain actual near-duplicates.…”
Section: )mentioning
confidence: 99%
See 2 more Smart Citations
“…• The video title, event title, and the four translations are submitted as search queries to the three target platforms (YouTube, Facebook, Twitter) and all results are aggregated in a common pool. • Using the near-duplicate retrieval algorithm of Kordopatis-Zilos et al [27], we filter the pool of videos in order to discard unrelated ones. • Finally a manual confirmation step is used to remove erroneous results of the automatic method and only retain actual near-duplicates.…”
Section: )mentioning
confidence: 99%
“…A viral video of a girl being chased by a bear while snowboarding was posted five days after the channel was created. The video gained millions of views before it was debunked 27 . The average number of videos per month uploaded by the channel is calculated by dividing the total number of videos posted by the channel to the number of months that this channel is alive.…”
Section: Number Of Verification Commentsmentioning
confidence: 99%
See 1 more Smart Citation
“…To observe no performance loss, a sufficiently large and diverse dataset to create vocabularies is required, which needs significant effort to be collected or sometimes is not even possible. Hence, we also developed a Deep Metric Learning (DML) approach to overcome this limitation [28]. This involves training a Deep Neural Network (DNN) to approximate an embedding function for the accurate computation of similarity between two candidate videos.…”
Section: Deep Metric Learning Approachmentioning
confidence: 99%
“…In Section 4.2, we review the related literature in the field of NDVR by providing an outline of the major trends in the field. In Section 4.3, we present the two aforementioned NDVR approaches that have been developed within the InVID project [27,28]. In Section 4.4, we report on the results of a comprehensive experimental study, including a comparison with five state-of-the-art methods.…”
Section: Introductionmentioning
confidence: 99%