Research
I'm interested in computer vision and machine learning, especially in 3D Vision and Deep Learning. Below are the highlighted peer-reviewed publications.
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Multiple Pose Virtual Try-On Based on 3D Clothing Reconstruction
Thai Thanh Tuan,
Matiur Rahman Minar,
Heejune Ahn,
John Wainwright
IEEE Access , 2021  
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We proposed a novel approach for image-based multi-pose virtual try-on (VTON) for fashion clothing, utilizing a hybrid method for 3D clothing reconstruction from single image.
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CloTH-VTON+: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON
Matiur Rahman Minar,
Thai Thanh Tuan,
Heejune Ahn
IEEE Access , 2021  
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We proposed a novel hybrid and fully automatic method for 3D clothing reconstruction from single image and applying it to image-based virtual try-on (VTON) for fashion clothing, which generates realistically deformed try-on results with superior quality.
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CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON
Matiur Rahman Minar,
Heejune Ahn
Asian Conference on Computer Vision , 2020 (ACCV 2020)  
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We proposed a novel hybrid and fully automatic method for 3D clothing reconstruction from single image and applying it to image-based virtual try-on (VTON) for fashion clothing, which generates realistically deformed try-on results with the highest possible quality.
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3D Reconstruction of Clothes using a Human Body Model and its Application to Image-based Virtual Try-On
Matiur Rahman Minar,
Thai Thanh Tuan,
Heejune Ahn,
Paul Rosin,
Yu-Kun Lai
CVPR Workshop on Computer Vision for Fashion, Art and Design , 2020 (CVPRW 2020)  
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We proposed a novel hybrid method for 3D clothing reconstruction and applying it to image-based virtual try-on (VTON) for fashion clothing, which generates realistically deformed try-on results.
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CP-VTON+: Clothing Shape and Texture Preserving Image-Based Virtual Try-On
Matiur Rahman Minar,
Thai Thanh Tuan,
Heejune Ahn,
Paul Rosin,
Yu-Kun Lai
CVPR Workshop on Computer Vision for Fashion, Art and Design , 2020 (CVPRW 2020)  
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We proposed CP-VTON+, a new pipeline for fully image-based virtual try-on (VTON) for fashion clothing, solving the limitations of state-of-the-art VTON approaches.
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Achievements
These include awards, challenges, and competitions.
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Miscellaneous
These include coursework, side projects, and regionally published, and unpublished research works.
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A Study on 3D reconstruction from clothing image and application to Virtual Try-On
Matiur Rahman Minar
MS Thesis, SeoulTech
February 2021
Manuscript
Master's thesis on the fashion-clothing based online virtual try-on project, exploring a hybrid approach to preserve the realism in the try-on output.
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3D Reconstruction of a Single Clothing Image and Its Application to Image-based Virtual Try-On
(Korean)
Heejune Ahn,
Matiur Rahman Minar
Journal of the Korea Industrial Information Systems Research, 2020  
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We proposed a novel hybrid method for 3D clothing reconstruction and applying it to image-based virtual try-on (VTON) for fashion clothing, which generates realistically deformed try-on results.
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An Improved VTON (Virtual-Try-On) Algorithm using a Pair of Cloth and Human Image
(Korean)
Matiur Rahman Minar,
Thai Thanh Tuan,
Heejune Ahn
Journal of the Korea Industrial Information Systems Research, 2020  
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code
We proposed a new pipeline for fully image-based virtual try-on for fashion clothing.
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Performance Evaluation of VTON (Virtual-Try-On) Algorithms using a Pair of Cloth and Human Image
(Korean)
Thai Thanh Tuan,
Matiur Rahman Minar,
Heejune Ahn
Journal of the Korea Industrial Information Systems Research, 2019  
paper
We analyzed and compared performances of the state-of-the-art image-based virtual try-on methods, their strengths and weaknesses.
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Fashion-show Animation Generation using a Single Image to 3D Human Reconstruction Technique
(Korean)
Heejune Ahn,
Matiur Rahman Minar
Journal of the Korea Industrial Information Systems Research, 2019  
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We reconstructed 3D fashion model out of single image and generated fashion-show walk motion-capture video.
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A Robust Pipeline for New Korean Vehicle License Plate Detection
Matiur Rahman Minar,
Meer Sadeq Billah,
Young-Gwang Cho
Machine Vision course, SeoulTech
Fall 2019
Worked on design and implementation of a robust pipeline for detecting new Korean vehicle number plates.
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Parsing Fashion Clothing
EMCOM Lab, SeoulTech
2018-2019
code
Semantic segmentation using state-of-the-art and improved models for fashion clothing datasets e.g. ATR, CFPD, LIP.
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Recent Advances in Deep Learning: An Overview
Matiur Rahman Minar,
Jibon Naher
CUET
July 2018
arXiv
An overview of Deep Learning, the state-of-the-art, recently proposed models and frameworks, and applications.
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