DECA
learning-topology-synthetic-data
| DECA | learning-topology-synthetic-data | |
|---|---|---|
| 5 | 5 | |
| 2,009 | 37 | |
| - | - | |
| 0.0 | 4.3 | |
| 9 months ago | 9 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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DECA
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Looking for a NLP expert to help me in a project about body movements and facial expressions.
[2] https://github.com/yfeng95/DECA
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[D] Alternatives to Mediapipe's FaceMesh for 3D Face Reconstruction
You can check DECA, 3DDFA , as they give you detailed 3d landmarks (detailed as in "denser" 3d landmarks) which is obtained through Face Blendshape Vertices.
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Automatic BlendShape Transfer to Different Topology!
But where else should he post seems like the post got deleted in many other places already. The pay link in the video description looks suspicious and was most likely not included in this video to prevent deletion. The Tool itself looks similar to thinks proposed in: https://github.com/YadiraF/DECA or something similar what Disney did.
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[P] Mapping an image to a 3D face model (iPhone AR compatible)
I retrained DECA using the original dataset and additional data that I generated and then combined this with a library I wrote to convert .obj files to .usdz, a format used on iPhone to describe 3D models that are compatible with its AR viewer.
- DECA: Detailed Expression Capture and Animation
learning-topology-synthetic-data
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Want to use synthetic data, but don't want to deal with domain gap?
For those interested, here are our source code with pretrained mdoels (it is light-weight so it runs on your local machine!) and arxiv version of our paper.
paper: https://arxiv.org/pdf/2106.02994.pdf
Here are some of the reconstructions produced by our method:
https://github.com/alexklwong/learning-topology-synthetic-da...
https://github.com/alexklwong/learning-topology-synthetic-da...
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[N][R] Want to leverage synthetic data for 3d reconstruction, but don't want to deal with the photometric domain gap? (ICRA 2021 talk)
Code for https://arxiv.org/abs/2106.02994 found: https://github.com/alexklwong/learning-topology-synthetic-data
What are some alternatives?
Blender-Tools-for-DSCS - This repository provides a work-in-progress addon for Blender 2.8 that can (to some degree) import model files from the PC version of Digimon Story: Cyber Sleuth. It provides new options in File > Import and File > Export named "DSCS Model", which should be pointed towards 'name' files in the game data. The file format is mostly understood; but some bugs remain and there are some Blender issues yet to be understood. Also has experimental support for the PS4 version, and for Megido72.
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
vrn - :man: Code for "Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression"
bpycv - Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
3DDFA_V2 - The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
student-teacher-anomaly-detection - Student–Teacher Anomaly Detection with Discriminative Latent Embeddings
facexlib - FaceXlib aims at providing ready-to-use face-related functions based on current STOA open-source methods.
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
3DDFA - The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.
Make-It-3D - [ICCV 2023] Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior
carveme - CarveMe: genome-scale metabolic model reconstruction
NeuralRecon - Code for "NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video", CVPR 2021 oral