hedlen / awesome-segment-anything Goto Github PK
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License: MIT License
Tracking and collecting papers/projects/others related to Segment Anything.
License: MIT License
Hi, thanks for your great work, very inspired ๐
Besides, I would like to draw your attention to one SAM application in the robotic field:
Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model
, where SAM is applied to obtain corresponding masks. The code is also open-sourced at https://github.com/OpenGVLab/Instruct2Act.
Hi,
Thanks for your great repo!
Could you please add our SAMPro3D into the 3D category?
It lifts SAM to 3D indoor scene segmentation, and does not require any training, tuning, or distillation. It achieves superior segmentation results.
Thanks a lot!
Implemented NanoSAM in cpp on Windows for real time segment anything applications:
https://github.com/spacewalk01/nanosam-cpp
Please add to your list the newly created TomoSAM extension of 3D Slicer. Here is the paper associated to it, and this is the video tutorial
We have made a new project to make SAM lightweight for mobile applications.
Could you please kindly include it here?
The link is as follows:
https://github.com/Hedlen/awesome-segment-anything/issues/new
Thanks for your help in advance.
Hi,
Could you please consider adding this project?
Segment Anything in Defect Dectection.
paper link:
https://arxiv.org/abs/2311.10245
code link:
https://github.com/bozhenhhu/DefectSAM
How to finetune the SAM on my custom dataset?
Hi,
could you please consider add this remote sensing project:
https://github.com/ggsDing/SAM-CD
paper link:
http://arxiv.org/abs/2309.01429
Thanks for meticulously maintaining this repository!
We would like to recommend our recent work on "Segment Any Point Cloud Sequences".
We introduce Seal, a framework capable of leveraging 2D vision foundation models for self-supervised learning on large-scale 3D point clouds.
Thanks a lot!
Thank you for your great collection!
I am the author of the paper "Medical SAM Adapter", and our code can actually be found at: https://github.com/KidsWithTokens/Medical-SAM-Adapter
It would be appreciated if you could add our code link, thank you very much.
Thank you for collecting these projects. Nice job!
There is another work about SAM based on CLIP's explainability to achieve text to mask without manual points.
https://github.com/xmed-lab/CLIP_Surgery
Besides, it enhances many open-vocabulary tasks, like segmentation, multi-label classification, multimodal visualization.
This is the jupyter demo:
https://github.com/xmed-lab/CLIP_Surgery/blob/master/demo.ipynb
A more engineer implement
https://github.com/Kingfish404/segment-anything-webui/
Demo for interactive without backend: https://segment-anything-webui.vercel.app/
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