Omkar2118/datasets huggingface dataset:
TextCaps

Contains 145k captions for 28k images. The dataset challenges a model to recognize text, relate it to its visual context, and decide what part of the text to copy or paraphrase, requiring spatial, semantic, and visual reasoning between multiple text tokens and visual entities, such as objects. 

Source: [TextCaps: a Dataset for Image Captioning with Reading Comprehension](/paper/textcaps-a-dataset-for-image-captioning-with)

Introducing paper: TextCaps: a Dataset for Image Captioning with Reading Comprehension
TextSeg

**TextSeg** is a large-scale fine-annotated and multi-purpose text detection and segmentation dataset, collecting scene and design text with six types of annotations: word- and character-wise bounding polygons, masks and transcriptions.

Source: [https://github.com/SHI-Labs/Rethinking-Text-Segmentation](https://github.com/SHI-Labs/Rethinking-Text-Segmentation)
Image Source: [https://github.com/SHI-Labs/Rethinking-Text-Segmentation](https://github.com/SHI-Labs/Rethinking-Text-Segmentation)

Introducing paper: Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach
Textual Visual Semantic Dataset

Extends the COCO-text [Veit et al. 2016] with information about the scene (such as objects and places appearing in the image) to enable researchers to include semantic relations between texts and scene in their Text Spotting systems, and to offer a common framework for such approaches.

Source: [Textual Visual Semantic Dataset for Text Spotting](/paper/textual-visual-semantic-dataset-for-text)

Introducing paper: Textual Visual Semantic Dataset for Text Spotting