instant-ngp
colmap
Our great sponsors
instant-ngp | colmap | |
---|---|---|
147 | 28 | |
15,329 | 6,720 | |
2.2% | 4.3% | |
6.7 | 9.2 | |
7 days ago | 6 days ago | |
Cuda | C++ | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
instant-ngp
- I want a 3d scanner...
-
Mind-blowing results (LORA/Checkpoint mix)
This is really cool! Could you now use something like this to turn the new images in a 3d model? Or even use open pose (controlnet) to generate a bunch of images from different angles and use InstantNeRF to make a 3d model for free!
-
Scanning in real life environments to be viewed in VR >>> taking pictures. Simple process from video -> render, using instant-ngp
It is at this point that you should have Instant-NGP setup. The script for the COLMAP processing is in the repo, as well as the steps to perform it. My exact parameters were 3 fps and 16 aabb. It is pretty helpful to add the scripts directory into path for exact access system-wide.
-
[D] NeRF, LeRF, Prolific Dreamer, Neuralangelo, and a lot of other cool NeRF research
[Project Page] https://nvlabs.github.io/instant-ngp/
-
Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields
instant-ngp ([1]) from NVIDIA can render NeRF in VR in real-time, assuming a very good desktop video card. Note that instant-ngp is not as photo-realistic as Zip-NeRF. But it's still very good!
1. https://github.com/NVlabs/instant-ngp
- How about Ranger Green?
-
Roast my MC kit
Playing around with neRF AI (https://github.com/NVlabs/instant-ngp) to create some 3d gear reveals. I think this a fun way to show off a kit, what do you think?
- Has anyone tried to generate images from enough angles to feed Nvidia Nerf to make 3D models?
-
Instant NPG: how do minimize noise and maximize quality? Tips welcome!
3 not sure if it's the one you want but the -aabb_scale is a crop. This page recommends trying a large value of 128 for some outdoor scenes: https://github.com/NVlabs/instant-ngp/blob/master/docs/nerf_dataset_tips.md
-
I NeRF'd the new Taco Bell on Rt. 40
I don't know about lumalabs, but basically all NeRF projects these days are based on NVIDIAs Instant neural graphics primitives ( GitHub: instant-ngp). It utilizes COLMAP for SfM (preprocessing step for the neural network) and runs on average Geforce cards pretty good. The fox example (50 photos) on their page literally takes 5 seconds to complete.
colmap
- Magic123: One Image to High-Quality 3D Object Generation
-
Drone mapping is pretty dang cool
Not saying its easy to use, but there is an application gui and it is free: https://github.com/colmap/colmap
-
Import many photogrammetry software's scenes into Blender
Colmap (Model folders (BIN and TXT), dense workspaces, NVM, PLY)
- Best options for monocular reconstruction?
-
improving camera pose estimation using multiple aruco markers
See colmap for example https://colmap.github.io/
-
2D images to 3D Object reconstruction
You're looking into a problem called photogrammetry, and a well-studied one at that. I'd recommend looking into "shape from motion" (sfm); specifically techniques that do "dense reconstruction." I'd recommend COLMAP to start with. It does pose estimation from images (e.g. you point it at a bunch of images and it will figure out the relative poses of the cameras that took them), as well as sparse and dense reconstcution.
-
Framework generate 3d meshes from camera images
COLMAP builds dense meshes from a collection of cameras https://colmap.github.io/
- Nerfstudio: A collaboration friendly studio for NeRFs
-
Neural Radiance Fields and input shape
I’ve seen references to using COLMAP (https://colmap.github.io/) to estimate camera position/pose, e.g. here
-
3D reconstruction of an object from videos/few images
Classical photogrammetry, where I agree with u/tdgros that the way to go is https://colmap.github.io/. There are actually better variants in literature but nothing is more reliable and user-friendly than COLMAP. This will give you a very precise point cloud, that can be meshed if needed.
What are some alternatives?
awesome-NeRF - A curated list of awesome neural radiance fields papers
Meshroom - 3D Reconstruction Software
tiny-cuda-nn - Lightning fast C++/CUDA neural network framework
OpenMVG (open Multiple View Geometry) - open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.
nerf-pytorch - A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
Hierarchical-Localization - Visual localization made easy with hloc
TensoRF - [ECCV 2022] Tensorial Radiance Fields, a novel approach to model and reconstruct radiance fields
nerf - Code release for NeRF (Neural Radiance Fields)
instant-meshes - Interactive field-aligned mesh generator
openMVS - open Multi-View Stereo reconstruction library
instant-ngp-Windows - Instant neural graphics primitives: lightning fast NeRF and more
OpenSfM - Open source Structure-from-Motion pipeline