A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning

Miguel G. San-Emeterio

doi:10.1007/978-3-031-13324-4_2

A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning

Miguel G. San-Emeterio^*

^*Corresponding author for this work

Atos Research and Innovation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

This review article about Few-Shot Learning techniques is focused on Computer Vision Applications based on Deep Convolutional Neural Networks. A general discussion about Few-Shot Learning is given, featuring a context-constrained description, a short list of applications, a description of a couple of commonly used techniques and a discussion of the most used benchmarks for FSL computer vision applications. In addition, the paper features a few examples of recent publications in which FSL techniques are used for training models in the context of Human Behaviour Analysis and Smart City Environment Safety. These examples give some insight about the performance of state-of-the-art FSL algorithms, what metrics do they achieve, and how many samples are needed for accomplishing that.

Original language	English
Title of host publication	Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Revised Selected Papers
Editors	Pier Luigi Mazzeo, Cosimo Distante, Emanuele Frontoni, Stan Sclaroff
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	14-25
Number of pages	12
ISBN (Print)	9783031133237
DOIs	https://doi.org/10.1007/978-3-031-13324-4_2
Publication status	Published - 2022
Externally published	Yes
Event	21st International Workshops on Image Analysis and Processing Workshops , ICIAP 2022 - Lecce, Italy Duration: 23 May 2022 → 27 May 2022

Publication series

Name	Lecture Notes in Computer Science
Volume	13374 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Workshops on Image Analysis and Processing Workshops , ICIAP 2022
Country/Territory	Italy
City	Lecce
Period	23/05/22 → 27/05/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Computer Vision
Deep Learning
Few-Shot Learning
Human Behaviour Analysis
Smart City Environment Safety

Access to Document

10.1007/978-3-031-13324-4_2

Cite this

San-Emeterio, M. G. (2022). A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning. In P. L. Mazzeo, C. Distante, E. Frontoni, & S. Sclaroff (Eds.), Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Revised Selected Papers (pp. 14-25). (Lecture Notes in Computer Science; Vol. 13374 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-13324-4_2

San-Emeterio, Miguel G. / A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning. Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Revised Selected Papers. editor / Pier Luigi Mazzeo ; Cosimo Distante ; Emanuele Frontoni ; Stan Sclaroff. Springer Science and Business Media Deutschland GmbH, 2022. pp. 14-25 (Lecture Notes in Computer Science).

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title = "A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning",

abstract = "This review article about Few-Shot Learning techniques is focused on Computer Vision Applications based on Deep Convolutional Neural Networks. A general discussion about Few-Shot Learning is given, featuring a context-constrained description, a short list of applications, a description of a couple of commonly used techniques and a discussion of the most used benchmarks for FSL computer vision applications. In addition, the paper features a few examples of recent publications in which FSL techniques are used for training models in the context of Human Behaviour Analysis and Smart City Environment Safety. These examples give some insight about the performance of state-of-the-art FSL algorithms, what metrics do they achieve, and how many samples are needed for accomplishing that.",

keywords = "Computer Vision, Deep Learning, Few-Shot Learning, Human Behaviour Analysis, Smart City Environment Safety",

author = "San-Emeterio, \{Miguel G.\}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 21st International Workshops on Image Analysis and Processing Workshops , ICIAP 2022 ; Conference date: 23-05-2022 Through 27-05-2022",

year = "2022",

doi = "10.1007/978-3-031-13324-4\_2",

language = "English",

isbn = "9783031133237",

series = "Lecture Notes in Computer Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

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San-Emeterio, MG 2022, A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning. in PL Mazzeo, C Distante, E Frontoni & S Sclaroff (eds), Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Revised Selected Papers. Lecture Notes in Computer Science, vol. 13374 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 14-25, 21st International Workshops on Image Analysis and Processing Workshops , ICIAP 2022, Lecce, Italy, 23/05/22. https://doi.org/10.1007/978-3-031-13324-4_2

A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning. / San-Emeterio, Miguel G.
Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Revised Selected Papers. ed. / Pier Luigi Mazzeo; Cosimo Distante; Emanuele Frontoni; Stan Sclaroff. Springer Science and Business Media Deutschland GmbH, 2022. p. 14-25 (Lecture Notes in Computer Science; Vol. 13374 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This review article about Few-Shot Learning techniques is focused on Computer Vision Applications based on Deep Convolutional Neural Networks. A general discussion about Few-Shot Learning is given, featuring a context-constrained description, a short list of applications, a description of a couple of commonly used techniques and a discussion of the most used benchmarks for FSL computer vision applications. In addition, the paper features a few examples of recent publications in which FSL techniques are used for training models in the context of Human Behaviour Analysis and Smart City Environment Safety. These examples give some insight about the performance of state-of-the-art FSL algorithms, what metrics do they achieve, and how many samples are needed for accomplishing that.

KW - Computer Vision

KW - Deep Learning

KW - Few-Shot Learning

KW - Human Behaviour Analysis

KW - Smart City Environment Safety

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A2 - Distante, Cosimo

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ER -

San-Emeterio MG. A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning. In Mazzeo PL, Distante C, Frontoni E, Sclaroff S, editors, Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2022. p. 14-25. (Lecture Notes in Computer Science). doi: 10.1007/978-3-031-13324-4_2

A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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