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Meshroom Alternatives
Similar projects and alternatives to Meshroom
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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OpenMVG (open Multiple View Geometry)
open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.
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ODM
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
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instant-ngp
Instant neural graphics primitives: lightning fast NeRF and more
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Blender-Addon-Photogrammetry-Importer
Addon to import different photogrammetry formats into Blender
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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meshroomcl
MeshroomCL: An OpenCL implementation of photogrammetry with the Meshroom interface
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tsdf-fusion-python
Python code to fuse multiple RGB-D images into a TSDF voxel volume.
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zpy
Synthetic data for computer vision. An open source toolkit using Blender and Python.
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FreeCAD
This is the official source code of FreeCAD, a free and opensource multiplatform 3D parametric modeler.
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awesome-virtual-try-on
A curated list of awesome research papers, projects, code, dataset, workshops etc. related to virtual try-on.
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MotioNet
A deep neural network that directly reconstructs the motion of a 3D human skeleton from monocular video [ToG 2020]
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Meshroom reviews and mentions
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Best way to work with point cloud files?
You could start by importing the point cloud model into a software with native support for the file format. Some open source examples are Meshroom (https://alicevision.org) or Meshlab (https://www.meshlab.net). There are other softwares from companies like Autodesk that might be more intuitive but you'd need licenses to use them. Rhino and Blender can handle the file formats but might struggle depending on the size and complexity.
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3D Novel View Synthesis with Diffusion Models
You're probably looking for multiview photogrammetry. Also known as "structure from motion." https://github.com/alicevision/Meshroom is a good free tool for this, but the most popular one is probably AGISoft MetaShape.
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MeshroomCL - This version of Meshroom doesn't require CUDA
huh? https://github.com/alicevision/meshroom
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NVIDIA's Instant-NGP is getting increasingly better. Took this NeRF in Bordeaux-Saint-Clair, Normandie, France. What do you think?
There is also 3DF Zephyr and Meshroom
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OpenDroneMap
Are you aware of solutions like Alicevision/Meshroom (MPLv2)?
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Where can I find Meshroom's SFM code?
I would like to understand how Meshroom works under the hood, but couldn't find the source code. There is the github project Meshroom Github, but it only consists of the frontend code and calls the prebuild binaries. Does Meshroom also publish the source code for those binaries or is it proprietary?
- Integrating multiple point clouds?
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Photorealistic Monocular 3D Reconstruction of Humans Wearing Clothing
I have been recently looking at several "3d scanning" from monocular images/videos solutions and although they make for impressive demos I'm afraid they are a few years away from robust results.
On one hand you have traditional photogrammetry based on classical image descriptors (from the beginning of the 2000s). A nice open source solution is Meshroom [1]. I have very little experience as I have just tinkered a little but I would say they work OK with geometry of medium complexity and detailed textures. They fail horribly with untextured objects, like for example a candle. They are semi-automatic: you upload some photos and run the pipepiline but for best results it's easy to tweak as there are a lot of knobs to try.
On the other hand you have these deep learning research papers. A lot of them have Colab notebooks you can try yourself (which is awesome, thank you). They can give you these very nice demos for some kind of objects (the ones we have a lot of training data, like human bodies), but they are not truly general and sometimes will generate artifacts. There is some opportunity here if they are integrated in a semi-supervised workflow, like this [2].
Anyway, just curious and not an expert.
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3D modelling just by walking around the object
This has been used in Video games for the Better part of decade, already. and you can do this yourself without an iphone with lidar, by taking a lot of pictures of an object from various angles, and then use something like meshroom to make a detailed 3d model of it.
This is using the Iphones LIDAR, (basiacally laser depth sensor) to get accurate data, but it can be done also be done without it, just with a lot of pictures of all around the object, from various angles, and some software like meshroom
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alicevision/Meshroom is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.