instant-ngp
prolificdreamer
instant-ngp | prolificdreamer | |
---|---|---|
147 | 5 | |
15,364 | 1,375 | |
1.1% | 1.5% | |
6.7 | 4.5 | |
14 days ago | 5 months ago | |
Cuda | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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instant-ngp
- I want a 3d scanner...
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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!
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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.
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[D] NeRF, LeRF, Prolific Dreamer, Neuralangelo, and a lot of other cool NeRF research
[Project Page] https://nvlabs.github.io/instant-ngp/
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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?
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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?
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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
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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.
prolificdreamer
- ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation
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Magic123: One Image to High-Quality 3D Object Generation
Interesting work! But given the time and complexity of the generation, I think VSD-loss based implementations have higher fidelity. See https://github.com/thu-ml/prolificdreamer or https://github.com/threestudio-project/threestudio/tree/main...
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[D] NeRF, LeRF, Prolific Dreamer, Neuralangelo, and a lot of other cool NeRF research
[Code] https://github.com/thu-ml/prolificdreamer
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Is it possible for me to approximate a depth map from a generated image and make a 3D model?
Personally, I'm waiting for code to drop for this one: https://github.com/thu-ml/prolificdreamer
What are some alternatives?
awesome-NeRF - A curated list of awesome neural radiance fields papers
hyperreel - Code release for HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Sampling
tiny-cuda-nn - Lightning fast C++/CUDA neural network framework
stable-diffusion-howto - Run Stable Diffusion on your M1 Mac’s GPU (Intel and non-Apple PCs are also supported)
nerf-pytorch - A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
instruct-pix2pix
TensoRF - [ECCV 2022] Tensorial Radiance Fields, a novel approach to model and reconstruct radiance fields
threestudio - A unified framework for 3D content generation.
colmap - COLMAP - Structure-from-Motion and Multi-View Stereo
BungeeNeRF - [ECCV22] BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-scale Scene Rendering
instant-meshes - Interactive field-aligned mesh generator
lerf - Code for LERF: Language Embedded Radiance Fields