ECON
neural-deferred-shading
| ECON | neural-deferred-shading | |
|---|---|---|
| 2 | 1 | |
| 1,023 | 239 | |
| - | 5.4% | |
| 5.2 | 4.6 | |
| 2 months ago | 2 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/
neural-deferred-shading
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Multi-View Mesh Reconstruction with Neural Deferred Shading
Github:https://github.com/fraunhoferhhi/neural-deferred-shading
What are some alternatives?
ICON - [CVPR'22] ICON: Implicit Clothed humans Obtained from Normals
GAN2Shape - Code for GAN2Shape (ICLR2021 oral)
agi2nerf - Simple tool for converting Agisoft XML files to NERF JSON files for https://github.com/NVlabs/instant-ngp
surface_normal_uncertainty - (ICCV 2021 - oral) Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
taichi-nerfs - Implementations of NeRF variants based on Taichi + PyTorch
MICA - MICA - Towards Metrical Reconstruction of Human Faces [ECCV2022]
PIFu - This repository contains the code for the paper "PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization"
3d-transforms - 3D Transforms is a library to easily work with 3D data and make 3D transformations. This library originally started as a few functions here and there for my own work which I then turned into a library.
Text2Video - ICASSP 2022: "Text2Video: text-driven talking-head video synthesis with phonetic dictionary".
2dimageto3dmodel - We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
BlenderNeRF - Easy NeRF synthetic dataset creation within Blender