YilmazKadir/Volt
[ECCV 2026 Long Oral] Volume Transformer: Revisiting Vanilla Transformers for 3D Scene Understanding
- Stars
- 192
- Forks
- 12
- Open issues
- 0
- Last push
- 1mo ago
Volt star history
-2 this week
About Volt
Volt is a free, open-source computer vision tool by YilmazKadir, written mainly in Python. [ECCV 2026 Long Oral] Volume Transformer: Revisiting Vanilla Transformers for 3D Scene Understanding. It has 192 GitHub stars and 12 forks, and was last updated 1mo ago. It's released under the MIT license, a standard open-source license. According to the project, it works on macOS.
- License
- MIT
- Commercial use
- Commercial OK
- Language
- Python
- Stars
- 192
- Last update
- 1mo ago
- Runs on Mac
- Yes (as stated by the project)
- GPU
- Not stated
- Paid API key
- Not stated
- Self-hostable
- Not stated
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Volt FAQ
Can I use Volt commercially?
Yes. MIT is a permissive license: commercial use is allowed as long as you keep the license notice. This is a plain-English summary, not legal advice.
Is Volt free?
Yes. Volt is open source and free to use. It's released under the MIT license, a standard open-source license.
Does Volt run on a Mac?
Yes. According to the project, Volt works on macOS.
Does Volt need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is Volt still maintained?
It was last updated 1mo ago. Check recent issues on GitHub to judge how active it is.
What are alternatives to Volt?
Similar free, open-source tools include ultralytics, segmentation_models.pytorch, yolov5, MonoScene.
Maintain Volt?
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