DECA
carveme
| DECA | carveme | |
|---|---|---|
| 5 | 2 | |
| 2,009 | 138 | |
| - | - | |
| 0.0 | 5.0 | |
| 9 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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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
carveme
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Advice on how to go about genome scale metabolic model construction
Carveme: https://academic.oup.com/nar/article/46/15/7542/5042022 https://github.com/cdanielmachado/carveme https://carveme.readthedocs.io/en/latest/usage.html
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metaGEM: create your own genome scale metabolic models directly from metagenomes
Thanks sharing, I believe I have seen the github repo/paper before! Looks very interesting, I wonder if mantis could be used for expanding the functional annotation of sequences in the BiGG database (paper). This is the database that is used by CarveMe (paper) for building metabolic models from protein fasta files within the metaGEM workflow. I believe that CarveMe does not actually use the annotations themselves, but simply aligns sequences in a fasta file to the BiGG database, which contains associations between sequences -> genes -> reactions -> metabolites.
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.
metaGEM - :gem: An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data
vrn - :man: Code for "Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression"
ancient-microbiome-denovo
3DDFA_V2 - The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
embl_gems - EMBL GEMs: A collection of GEnome-scale Models for bacterial species
facexlib - FaceXlib aims at providing ready-to-use face-related functions based on current STOA open-source methods.
StrayVisualizer - Visualize Data From Stray Scanner https://keke.dev/blog/2021/03/10/Stray-Scanner.html
learning-topology-synthetic-data - Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
deepdiff - DeepDiff: Deep Difference and search of any Python object/data. DeepHash: Hash of any object based on its contents. Delta: Use deltas to reconstruct objects by adding deltas together.
3DDFA - The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.
deviceidentifier-py - Utils to manipulate and learn from assorted device identifier formats via Reincubate's API.