ECON
PIFu
ECON | PIFu | |
---|---|---|
2 | 3 | |
1,023 | 1,734 | |
- | - | |
5.2 | 0.0 | |
2 months ago | 6 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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ECON
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ECON: Explicit Clothed humans Optimized via Normal integration
I think you forgot the content https://github.com/YuliangXiu/ECON
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Latest Artificial Intelligence (AI) Research Proposes ECON, A Method To Reconstruct Detailed Clothed 3D Humans From A Color Image
Quick Read: https://www.marktechpost.com/2022/12/19/latest-artificial-intelligence-ai-research-proposes-econ-a-method-to-reconstruct-detailed-clothed-3d-humans-from-a-color-image/ Paper: https://arxiv.org/pdf/2212.07422.pdf Github: https://github.com/YuliangXiu/ECON Project: https://xiuyuliang.cn/econ/
PIFu
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I scanned myself with Reality Capture but the 3D model is messy. Is there any way to clean it up with AI or something like that?
In terms of AI tools, you could try this: https://github.com/shunsukesaito/PIFu
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Any helpful links for rendering a 3D object from a picture of a person?
I realize this isn't the same as photogrammetry but the one (https://github.com/shunsukesaito/PIFu) I've been able to implement renders inaccurate/rough 3D objects as results.
- Does anyone know what plugin this is called that turns images into 3D is called?
What are some alternatives?
ICON - [CVPR'22] ICON: Implicit Clothed humans Obtained from Normals
stable-fashion - Stable Fashion: A prompt based virtual try on repository
agi2nerf - Simple tool for converting Agisoft XML files to NERF JSON files for https://github.com/NVlabs/instant-ngp
Pix2Vox - The official implementation of "Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images". (Xie et al., ICCV 2019)
taichi-nerfs - Implementations of NeRF variants based on Taichi + PyTorch
rs-mainspring-winder - Free design of a 3D printed watch mainspring winder with a rising sun knurling pattern.
neural-deferred-shading - Multi-View Mesh Reconstruction with Neural Deferred Shading (CVPR 2022)
Text2Video - ICASSP 2022: "Text2Video: text-driven talking-head video synthesis with phonetic dictionary".