3D human face portraits generation with mobile devices
This report presents the overview and implementation of techniques for generating 3D human face portraits using mobile devices. The primary focus is on two models: the Hierarchical Representation Network (HRN) and the Tensorial Radiance Fields (TensoRF). These advanced models aim to enhance the qual...
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2024
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sg-ntu-dr.10356-1816432024-12-13T15:45:43Z 3D human face portraits generation with mobile devices Dong, Jijun Alex Chichung Kot School of Electrical and Electronic Engineering EACKOT@ntu.edu.sg Engineering This report presents the overview and implementation of techniques for generating 3D human face portraits using mobile devices. The primary focus is on two models: the Hierarchical Representation Network (HRN) and the Tensorial Radiance Fields (TensoRF). These advanced models aim to enhance the quality of 3D face reconstruction. The HRN model applies hierarchical representations to capture intricate facial features with better precision. TensoRF utilises neural radiance fields to enhance the reconstruction process and achieve a 3D face reconstruction model. Multiple experiments and optimisations will be conducted on both models to improve their accuracy, realism, and performance. Through comparative analysis, insight into further advancements in 3D face reconstruction will be offered. Bachelor's degree 2024-12-11T23:11:41Z 2024-12-11T23:11:41Z 2024 Final Year Project (FYP) Dong, J. (2024). 3D human face portraits generation with mobile devices. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/181643 https://hdl.handle.net/10356/181643 en A3299-232 application/pdf Nanyang Technological University |
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This report presents the overview and implementation of techniques for generating 3D human face portraits using mobile devices. The primary focus is on two models: the Hierarchical Representation Network (HRN) and the Tensorial Radiance Fields (TensoRF). These advanced models aim to enhance the quality of 3D face reconstruction. The HRN model applies hierarchical representations to capture intricate facial features with better precision. TensoRF utilises neural radiance fields to enhance the reconstruction process and achieve a 3D face reconstruction model. Multiple experiments and optimisations will be conducted on both models to improve their accuracy, realism, and performance. Through comparative analysis, insight into further advancements in 3D face reconstruction will be offered. |
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Alex Chichung Kot |
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Alex Chichung Kot Dong, Jijun |
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Final Year Project |
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Dong, Jijun |
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Dong, Jijun |
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3D human face portraits generation with mobile devices |
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3D human face portraits generation with mobile devices |
title_full |
3D human face portraits generation with mobile devices |
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3D human face portraits generation with mobile devices |
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3D human face portraits generation with mobile devices |
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3d human face portraits generation with mobile devices |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/181643 |
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