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Use HF papers (#38184)

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* Use hf papers

* Hugging Face papers

* doi to hf papers

* style
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Quentin Gallouédec
2025-06-13 13:07:09 +02:00
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@@ -30,7 +30,7 @@ You can do so by running the following command: `pip install -U transformers==4.
## Overview
The DETA model was proposed in [NMS Strikes Back](https://arxiv.org/abs/2212.06137) by Jeffrey Ouyang-Zhang, Jang Hyun Cho, Xingyi Zhou, Philipp Krähenbühl.
The DETA model was proposed in [NMS Strikes Back](https://huggingface.co/papers/2212.06137) by Jeffrey Ouyang-Zhang, Jang Hyun Cho, Xingyi Zhou, Philipp Krähenbühl.
DETA (short for Detection Transformers with Assignment) improves [Deformable DETR](deformable_detr) by replacing the one-to-one bipartite Hungarian matching loss
with one-to-many label assignments used in traditional detectors with non-maximum suppression (NMS). This leads to significant gains of up to 2.5 mAP.
@@ -41,7 +41,7 @@ The abstract from the paper is the following:
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/deta_architecture.jpg"
alt="drawing" width="600"/>
<small> DETA overview. Taken from the <a href="https://arxiv.org/abs/2212.06137">original paper</a>. </small>
<small> DETA overview. Taken from the <a href="https://huggingface.co/papers/2212.06137">original paper</a>. </small>
This model was contributed by [nielsr](https://huggingface.co/nielsr).
The original code can be found [here](https://github.com/jozhang97/DETA).