Image2Life: A Model for 3D Mesh Reconstruction from a Single-Image

Lynda Ayachi, Mohamed Rabia Benarbia

2025

Abstract

Reconstructing 3D models from a single 2D image is a complex yet fascinating challenge with applications in areas like computer vision, robotics, and augmented reality. In this work, we propose a novel approach to tackle this problem, focusing on creating accurate and detailed 3D representations from minimal input. Our model combines advanced deep learning techniques with geometry-aware methods to extract and translate meaningful features from 2D images into 3D shapes. By introducing a new framework for feature extraction and a carefully designed decoding architecture, our method captures intricate details and improves the overall reconstruction quality. We tested the model extensively on well-known datasets, and the results show significant improvements compared to existing methods in terms of accuracy and reliability.

Paper Citation

in Harvard Style

Ayachi L. and Benarbia M. (2025). Image2Life: A Model for 3D Mesh Reconstruction from a Single-Image. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 1319-1326. DOI: 10.5220/0013349500003890

in Bibtex Style

@conference{icaart25,
author={Lynda Ayachi and Mohamed Benarbia},
title={Image2Life: A Model for 3D Mesh Reconstruction from a Single-Image},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={1319-1326},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013349500003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Image2Life: A Model for 3D Mesh Reconstruction from a Single-Image
SN - 978-989-758-737-5
AU - Ayachi L.
AU - Benarbia M.
PY - 2025
SP - 1319
EP - 1326
DO - 10.5220/0013349500003890
PB - SciTePress