Paper Title

DEEP LEARNING MEETS FASHION - A LOOK INTO VIRTUAL TRY-ON SOLUTIONS

Article Identifiers

Registration ID: IJNRD_217775

Published ID: IJNRD2404261

DOI: Click Here to Get

Authors

AMOS VIYANIKARAN J , CAROLINE VIOLA STELLA MARY M

Keywords

Deep Neural Networks, Convolutional Neural Networks, Computer Vision, VITON, GAN, STN

Abstract

Virtual Try-on for Clothes using Deep Neural Networks has been an active area of research in recent years. With the advancement of computer vision and deep learning techniques, it is now possible to create realistic simulations of clothing items on human bodies, allowing customers to try on clothes virtually before making a purchase. This technology has the potential to revolutionize the way we shop for clothes, saving time and reducing waste. In this paper, we review the state-of-the-art virtual try-on techniques and discuss the challenges and limitations of this technology. We also propose a new approach based on a deep neural network architecture that can accurately simulate the fit and appearance of clothing items on different body types. Our proposed method outperforms existing techniques in terms of realism and accuracy and can be used as a tool for virtual wardrobe management, online shopping, and personalized styling.

How To Cite (APA)

AMOS VIYANIKARAN J & CAROLINE VIOLA STELLA MARY M (April-2024). DEEP LEARNING MEETS FASHION - A LOOK INTO VIRTUAL TRY-ON SOLUTIONS. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), c281-c286. https://ijnrd.org/papers/IJNRD2404261.pdf

Issue

Volume 9 Issue 4, April-2024

Pages : c281-c286

Other Publication Details

Paper Reg. ID: IJNRD_217775

Published Paper Id: IJNRD2404261

Downloads: 000121991

Research Area: Science & Technology

Country: Tuticorin, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404261.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404261

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

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