Virtual Trial Room with Computer Vision and Machine Learning
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Abstract (arXiv)
Online shopping has revolutionized the retail industry, providing customers with convenience and accessibility. However, customers often hesitate to purchase wearable products such as watches, jewelry, glasses, shoes, and clothes due to the lack of certainty regarding fit and suitability. This leads to significant return rates, causing problems for both customers and vendors. To address this issue, a platform called the Virtual Trial Room with Computer Vision and Machine Learning is designed which enables customers to easily check whether a product will fit and suit them or not. To achieve this, an AI-generated 3D model of the human head was created from a single 2D image using the DECA model. This 3D model was then superimposed with a custom-made 3D model of glass which is based on real-world measurements and fitted over the human head. To replicate the real-world look and feel, the model was retouched with textures, lightness, and smoothness. Furthermore, a full-stack application was developed utilizing various fornt-end and back-end technologies. This application enables users to view 3D-generated results on the website, providing an immersive and interactive experience.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 25 references that are in the map. First posted on arXiv 14 Dec 2024.
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8 of 25 references.
References · 8
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- 2020Learning an Animatable Detailed 3D Face Model from In-The-Wild Imagescited by 477
- 2020Towards Fast, Accurate and Stable 3D Dense Face Alignmentcited by 219
- 2018Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Networkcited by 195
- 2019Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervisioncited by 176
- 2016Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Networkcited by 109
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