Matiur Rahman Minar

I am currently working as a Machine Learning Engineer. I completed MS from SeoulTech, where I worked on computer vision and deep learning under the supervision of Prof. Heejune Ahn. Previously, completed my Bachelor in CSE from BUET.

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Research

I'm interested in computer vision and machine learning, especially in 3D Vision and Deep Learning. Below are the highlighted peer-reviewed publications.

project image Multiple Pose Virtual Try-On Based on 3D Clothing Reconstruction
Thai Thanh Tuan, Matiur Rahman Minar, Heejune Ahn, John Wainwright
IEEE Access , 2021  
paper / bibtex

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.

project image CloTH-VTON+: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON
Matiur Rahman Minar, Thai Thanh Tuan, Heejune Ahn
IEEE Access , 2021  
project page / paper / bibtex

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.

project image 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)  
project page / paper / supplementary / video / bibtex

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.

project image 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)  
project page / paper / video / slide / bibtex

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.

project image 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)  
project page / paper / code, model & data / video / slide / bibtex

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.


Achievements

These include awards, challenges, and competitions.

project image The 4th Look Into Person (LIP) Challenge - Track 3 Image-based Multi-pose Virtual Try-on Challenge
Thai Thanh Tuan, Matiur Rahman Minar, Heejune Ahn
CVPR Workshop on Towards Human-Centric Image/Video Synthesis, and the 4th Look Into Person (LIP) Challenge, 2020 (CVPR 2020)
2nd place winner
workshop / challenge

Worked on design and implementation of a multi-pose guided image-based virtual try-on framework, trained on MPV dataset. We were evaluated 1st on SSIM metric, and 2nd on AMT study.


Miscellaneous

These include coursework, side projects, and regionally published, and unpublished research works.

MS Thesis 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.

project image 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  
paper / video / code

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.

project image 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  
paper / code

We proposed a new pipeline for fully image-based virtual try-on for fashion clothing.

project image 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.

project image 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  
paper / video / code

We reconstructed 3D fashion model out of single image and generated fashion-show walk motion-capture video.

project image 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.

project image 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.

project image 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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