FS_Deformable_DETR | Deformable_DETR on FSOD
kandi X-RAY | FS_Deformable_DETR Summary
kandi X-RAY | FS_Deformable_DETR Summary
FS_Deformable_DETR is a Python library. FS_Deformable_DETR has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
TL; DR. Deformable DETR is an efficient and fast-converging end-to-end object detector. It mitigates the high complexity and slow convergence issues of DETR via a novel sampling-based efficient attention mechanism. Abstract. DETR has been recently proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance. However, it suffers from slow convergence and limited feature spatial resolution, due to the limitation of Transformer attention modules in processing image feature maps. To mitigate these issues, we proposed Deformable DETR, whose attention modules only attend to a small set of key sampling points around a reference. Deformable DETR can achieve better performance than DETR (especially on small objects) with 10× less training epochs. Extensive experiments on the COCO benchmark demonstrate the effectiveness of our approach.
TL; DR. Deformable DETR is an efficient and fast-converging end-to-end object detector. It mitigates the high complexity and slow convergence issues of DETR via a novel sampling-based efficient attention mechanism. Abstract. DETR has been recently proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance. However, it suffers from slow convergence and limited feature spatial resolution, due to the limitation of Transformer attention modules in processing image feature maps. To mitigate these issues, we proposed Deformable DETR, whose attention modules only attend to a small set of key sampling points around a reference. Deformable DETR can achieve better performance than DETR (especially on small objects) with 10× less training epochs. Extensive experiments on the COCO benchmark demonstrate the effectiveness of our approach.
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Support
FS_Deformable_DETR has a low active ecosystem.
It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
FS_Deformable_DETR has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of FS_Deformable_DETR is current.
Quality
FS_Deformable_DETR has no bugs reported.
Security
FS_Deformable_DETR has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
FS_Deformable_DETR is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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FS_Deformable_DETR releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
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FS_Deformable_DETR Key Features
No Key Features are available at this moment for FS_Deformable_DETR.
FS_Deformable_DETR Examples and Code Snippets
No Code Snippets are available at this moment for FS_Deformable_DETR.
Community Discussions
No Community Discussions are available at this moment for FS_Deformable_DETR.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install FS_Deformable_DETR
You can download it from GitHub.
You can use FS_Deformable_DETR like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use FS_Deformable_DETR like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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