curated-list-of-awesome-3D-Morphable-Model-software-and-data
nvdiffrec
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| curated-list-of-awesome-3D-Morphable-Model-software-and-data | nvdiffrec | |
|---|---|---|
| 2 | 13 | |
| 845 | 2,043 | |
| 0.0% | 1.5% | |
| 1.8 | 4.8 | |
| over 1 year ago | 4 months ago | |
| Python | ||
| - | GNU General Public License v3.0 or later |
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curated-list-of-awesome-3D-Morphable-Model-software-and-data
- Blender animation augmented with AI
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[D] What is the current state of the art in 2D -> 3D Morphable Face Modes
This is designed to give you a good overview :) https://arxiv.org/abs/1909.01815 and this contains all shared codebases and datasets (please add to it if something is missing) https://github.com/3d-morphable-models/curated-list-of-awesome-3D-Morphable-Model-software-and-data/pulse
nvdiffrec
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[D] Found top conference papers using test data for validation.
It depends on which CV research you’re in. In NeRF view synthesis, it’s pretty common to use test sets as validation sets. This has been done in several papers, including oral papers.
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3D NeRF of a footstool
I think there came a paper recently nerf2mesh, which I still have to evaluate (but haven't found time yet). There's also https://github.com/NVlabs/nvdiffrec/. And there's cool easy-to-use research software like nerfstudio (at least if you compare it to a lot of the raw code releases from research papers).
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Fitting the texture from an image to the corresponding 3D model
For your use case, why is your model devoid of texture? You can try 3D scanning your desired object so that it comes with texture. Either that or use Nvidia's MoMA here to get your object from images.
- WHAT IS THE PROBLEM ???? HELP ME PLZ!!
- Blender animation augmented with AI
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[R] BUNGEENeRF: progressive neural radiance field for extreme multi-scale scene rendering
Have you seen this project: https://github.com/NVlabs/nvdiffrec (I haven't tried it). Also videos tend to have compression. If you can get images you'll get higher quality results with most photogrammetry software. Projects like meshroom are probably better for this if you have high quality pictures. There's a few articles that cover high quality scans that can help also.
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is NeRF photogrammetry? please don't call me old, but this technology, in my mind, does not fit the strict concept.
You can generate an accurate mesh from a NeRF: https://github.com/NVlabs/nvdiffrec, and measure from that.
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NeRF export options and pgrammetry application question
NERF specifically generates a radiance field, but there are research codes for turning that into a mesh (https://github.com/NVlabs/nvdiffrec) (not easy to use yet)
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[D] nvdiffrec setup
Hi, I'm not sure if this is the right place, but I was looking into seeing what the latest photo to model reconstruction looks like from here with NVIDIA (ArXiV paper is included there). There's a couple of neat examples, and after one dumb mistake setup was pretty easy. However, the meshes are not converging except very loosely when using the examples from the paper.
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nvdiffrec tutorial?
Hi everyone! I'm not sure this is the right place to ask, but I've been drooling over these cool ml and deep learning techniques showcased in videos. I was wondering if anyone could help me out in getting something like nvdiffrec to work with my own sample. https://github.com/NVlabs/nvdiffrec
What are some alternatives?
RENDER96-HD-TEXTURE-PACK - we'd like to think of this texture pack as a resource also, if you want to give sm64 your own look feel free to use these as a base for accuracy, just credit them render96 boys & girls
nvdiffrast - Nvdiffrast - Modular Primitives for High-Performance Differentiable Rendering
awesome-tiny-object-detection - 🕶 A curated list of Tiny Object Detection papers and related resources.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
cherry-mx-keycaps - 3D models of keycaps in cherry profile.
differentiable_volumetric_rendering - This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"
Face Recognition - The world's simplest facial recognition api for Python and the command line
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
3D-Machine-Learning - A resource repository for 3D machine learning
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Photogrammetry-Guide - Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.
visioStencils - A 3,400 visio :art: shapes, stencils, symbols, and icons collection to visually represent IT infrastructure