awesome-NeRF
A curated list of awesome neural radiance fields papers (by awesome-NeRF)
awesome-visual-slam
:books: The list of vision-based SLAM / Visual Odometry open source, blogs, and papers (by tzutalin)
| awesome-NeRF | awesome-visual-slam | |
|---|---|---|
| 18 | 2 | |
| 6,250 | 2,111 | |
| 0.9% | - | |
| 6.9 | 0.0 | |
| 1 day ago | almost 2 years ago | |
| TeX | ||
| MIT License | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
awesome-NeRF
Posts with mentions or reviews of awesome-NeRF.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-05.
- Recommendation for a convenient NERF model to try out? And discussions...
- This is not drone footage or an iPhone video but An AI model made this. Google researchers created this 3D scene and walkthrough using just 2D images. This is called a NeRF (Anti-Aliased Grid-Based Neural Radiance Fields), where AI models can take 2D pictures and create 3D scenes.
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New AI Tools for iPhones: Motion Capture and Environment Scanning - But What About Android Users?
And plenty others from outside Google Research. However, I wasn't aware there was a whole product making the creation of them trivial already. It's great to see honestly as I was hoping this would make the leap from research to products given how useful it is.
-
Is Nerf better than COLMAP for object reconstruction?
You can extract a mesh from a NeRF by using the marching cubes algorithm. But you'll have to texture it as well, and only after that can you be real time. NeRF training or inference isn't fast in the vanilla version. I suggest you browse https://github.com/awesome-NeRF/awesome-NeRF and look for the fast versions, this one is very fast, if you're ok with special CUDA kernels: https://nvlabs.github.io/instant-ngp/
- I volunteered to help out with the Awesome NeRF list - help me bring it up to date.
-
Nerf meshes are crap and thats normal right ?
There are implementations of NeRF that are solely based on the aim of a good export, and the work is going fast. I'm mobile right now but think this is a good place to watch, if my bookmarks are correct: https://github.com/yenchenlin/awesome-NeRF
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Nvidia NeRF
https://github.com/yenchenlin/awesome-NeRF watch and learn from this page!
- A curated list of NeRF papers & other resources
awesome-visual-slam
Posts with mentions or reviews of awesome-visual-slam.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-14.
-
what softwear like Dot3d can I use to map out a room with my I tel realsence depth camera?
What you are looking for is a SLAM library, which stands for simultaneous localization and mapping. Checkout these project list for more details, https://github.com/tzutalin/awesome-visual-slam
-
Real-Time Coherent 3D Reconstruction from Monocular Video
I don't think that's true. The paper says that camera pose estimated by a SLAM system is required. ARKit implements SLAM and can easily provide camera pose for each frame through the ARFrame class. But there are countless other implementations of SLAM, including Android ARCore, Oculus Quest, Roomba, self-driving cars, and a number of GitHub repos (https://github.com/tzutalin/awesome-visual-slam).
What are some alternatives?
When comparing awesome-NeRF and awesome-visual-slam you can also consider the following projects:
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
learn-ruby-and-cs - Books and other resources for learning Ruby and computer science. [Moved to: https://github.com/fpsvogel/learn-ruby]
colmap - COLMAP - Structure-from-Motion and Multi-View Stereo
hdl_graph_slam - 3D LIDAR-based Graph SLAM
nerf - Code release for NeRF (Neural Radiance Fields)
learn-ruby - Learning resources for Ruby, Rails, and related skills.
gaugan - Photorealistic landscape drawings using the Nvidia SPADE model
svox2 - Plenoxels: Radiance Fields without Neural Networks
sketch-to-art - 🖼 Create artwork from your casual sketch with GAN and style transfer
Parsec-Cloud-Preparation-Too
Parsec-Cloud-Preparation-Tool - Launch Parsec enabled cloud computers via your own cloud provider account.
DONERF - Code for "DONeRF Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks"
awesome-NeRF vs instant-ngp
awesome-visual-slam vs learn-ruby-and-cs
awesome-NeRF vs colmap
awesome-visual-slam vs hdl_graph_slam
awesome-NeRF vs nerf
awesome-visual-slam vs learn-ruby
awesome-NeRF vs gaugan
awesome-NeRF vs svox2
awesome-NeRF vs sketch-to-art
awesome-NeRF vs Parsec-Cloud-Preparation-Too
awesome-NeRF vs Parsec-Cloud-Preparation-Tool
awesome-NeRF vs DONERF