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Awesome Detection Transformer
Awesome Detection Transformer collects research papers on transformer methods for object detection and segmentation.
About Awesome Detection Transformer
Awesome Detection Transformer is a GitHub repository maintained by IDEA-Research that collects papers about transformers for detection and segmentation in computer vision. The repository states that entries are reorganized by research fields and provides a table of contents for navigation.
You can browse sections for DETR, object detection, open vocabulary and multi-modal object detection, 3D object detection, segmentation, pose estimation, and benchmarks. Many entries include the paper title, authors, and venue, with links to the paper and code. A toolbox section lists detrex for transformer-based detectors including DETR variants, and mmdetection for object detection including DETR and Deformable DETR.
It suits researchers, students, and developers who track transformer methods for object detection and segmentation and want references to papers and implementations in one place. If you find overlooked papers or resources, the repository asks you to open an issue or pull request.
Key features
- Collects papers on transformer detection and segmentation
- Organized by research fields and topics
- Includes DETR and object detection sections
- Links to papers and code implementations
- Lists detrex and mmdetection toolboxes
- Accepts contributions via issues and pull requests
Best for: Researchers and students tracking transformer methods for object detection and segmentation.
Good for
- Organized by research field
- Links to papers and code
- Covers detection, segmentation, and related tasks
Awesome Detection Transformer at a glance
- Category
- Research & Data › Academic Papers
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Awesome Detection Transformer FAQ
What is Awesome Detection Transformer?
It is a GitHub repository from IDEA-Research that collects papers about transformers for detection and segmentation in computer vision.
What topics does it cover?
It covers DETR, object detection, open vocabulary and multi-modal detection, 3D object detection, segmentation, pose estimation, and benchmarks.
Does it include code links?
Yes, many paper entries include links to the paper and code, and a toolbox section lists detrex and mmdetection.
Can I suggest missing papers?
Yes, the repository asks users to open issues or pull requests to add overlooked papers or resources.
Is something wrong or out of date?
Tell us and an editor will check it.
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