Make-It-3D
nerfstudio
| Make-It-3D | nerfstudio | |
|---|---|---|
| 1 | 10 | |
| 1,700 | 8,725 | |
| - | 2.7% | |
| 6.9 | 9.5 | |
| 8 months ago | 2 days ago | |
| Python | Python | |
| - | Apache License 2.0 |
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Make-It-3D
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Meet Make-it-3D: An Artificial Intelligence (AI) Framework For High-Fidelity 3D Object Generation From A Single Image
Github: https://github.com/junshutang/Make-It-3D
nerfstudio
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Smerf: Streamable Memory Efficient Radiance Fields
You’re under the right paper for doing this. Instead of one big model, they have several smaller ones for regions in the scene. This way rendering is fast for large scenes.
This is similar to Block-NeRF [0], in their project page they show some videos of what you’re asking.
As for an easy way of doing this, nothing out-of-the-box. You can keep an eye on nerfstudio [1], and if you feel brave you could implement this paper and make a PR!
[0] https://waymo.com/intl/es/research/block-nerf/
[1] https://github.com/nerfstudio-project/nerfstudio
- Researchers create open-source platform for Neural Radiance Field development
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first attempt to photogrammetry using DJI mini 2 and metashape. 460 images manual. What did I do wrong? What can i do to improve it? Would appreciate all kinds of advice to a newbie
Try rendering NERFs with your footage, you're gonna love the result and NERFs are pretty robust to reflections. You can use your Metashape solve for Nerf Studio https://github.com/nerfstudio-project/nerfstudio
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What is the best way to create a dataset for NeRF?
Beyond these tips, I don't have much. There's lots of research about how to improve quality of solves in the software itself. I'm hoping these get added to instant-ngp, since it's fast and free, but it is research software, not a product, so we'll see. Another thing to maybe look at is Nerfstudio. It can use instant-ngp as a solver, but there are other solvers. I briefly tried it but couldn't figure out how it worked, from the small bit of time I spent with it. I hope to get back to it.
- Nerfstudio – A collaboration friendly studio for NeRFs
- When the client's management is happy but their dev team is a pain
- A collaboration friendly studio for NeRFs
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NeRF ➜ point cloud export — now available via nerfstudio
nerf.studio | github | discord
- Show HN: A collaboration friendly studio for NeRFs
What are some alternatives?
DreamCraft3D - [ICLR 2024] Official implementation of DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
multinerf - A Code Release for Mip-NeRF 360, Ref-NeRF, and RawNeRF
NeuralRecon - Code for "NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video", CVPR 2021 oral
TorchSharp - A .NET library that provides access to the library that powers PyTorch.
SegmentAnythingin3D - Segment Anything in 3D with NeRFs (NeurIPS 2023)
sdfstudio - A Unified Framework for Surface Reconstruction
learning-topology-synthetic-data - Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
smerf-3d
AvatarPoser - Official Code for ECCV 2022 paper "AvatarPoser: Articulated Full-Body Pose Tracking from Sparse Motion Sensing"
vision_transformer
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)
kaolin-wisp - NVIDIA Kaolin Wisp is a PyTorch library powered by NVIDIA Kaolin Core to work with neural fields (including NeRFs, NGLOD, instant-ngp and VQAD).