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## Overview
The TextNet model was proposed in [FAST: Faster Arbitrarily-Shaped Text Detector with Minimalist Kernel Representation](https://arxiv.org/abs/2111.02394) by Zhe Chen, Jiahao Wang, Wenhai Wang, Guo Chen, Enze Xie, Ping Luo, Tong Lu. TextNet is a vision backbone useful for text detection tasks. It is the result of neural architecture search (NAS) on backbones with reward function as text detection task (to provide powerful features for text detection).
The TextNet model was proposed in [FAST: Faster Arbitrarily-Shaped Text Detector with Minimalist Kernel Representation](https://huggingface.co/papers/2111.02394) by Zhe Chen, Jiahao Wang, Wenhai Wang, Guo Chen, Enze Xie, Ping Luo, Tong Lu. TextNet is a vision backbone useful for text detection tasks. It is the result of neural architecture search (NAS) on backbones with reward function as text detection task (to provide powerful features for text detection).
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/fast_architecture.png"
alt="drawing" width="600"/>
<small> TextNet backbone as part of FAST. Taken from the <a href="https://arxiv.org/abs/2111.02394">original paper.</a> </small>
<small> TextNet backbone as part of FAST. Taken from the <a href="https://huggingface.co/papers/2111.02394">original paper.</a> </small>
This model was contributed by [Raghavan](https://huggingface.co/Raghavan), [jadechoghari](https://huggingface.co/jadechoghari) and [nielsr](https://huggingface.co/nielsr).