Omkar2118/datasets huggingface dataset:
ShareGPT4V

The **ShareGPT4V dataset** is a pioneering large-scale resource that features **1.2 million highly descriptive captions**. These captions surpass existing datasets in terms of **diversity and information content**. They cover a wide range of topics, including **world knowledge**, **object properties**, **spatial relationships**, and **aesthetic evaluations**². The dataset was introduced to address bottlenecks in large multi-modal models and enhance their performance by providing better captions².

Source: Conversation with Bing, 3/19/2024
(1) ShareGPT4V: Improving Large Multi-Modal Models with Better Captions. https://arxiv.org/pdf/2311.12793.pdf.
(2) openchat/openchat_sharegpt4_dataset · Datasets at Hugging Face. https://huggingface.co/datasets/openchat/openchat_sharegpt4_dataset.
(3) openchat/openchat_sharegpt_v3 · Datasets at Hugging Face. https://huggingface.co/datasets/openchat/openchat_sharegpt_v3.
(4) RyokoAI/ShareGPT52K · Datasets at Hugging Face. https://huggingface.co/datasets/RyokoAI/ShareGPT52K.

Introducing paper: ShareGPT4V: Improving Large Multi-Modal Models with Better Captions
Covid-19 radiography database

A team of researchers from Qatar University, Doha, Qatar, and the University of Dhaka, Bangladesh along with their collaborators from Pakistan and Malaysia in collaboration with medical doctors have created a database of chest X-ray images for COVID-19 positive cases along with Normal and Viral Pneumonia images. This COVID-19, normal, and other lung infection dataset is released in stages. In the first release, we have released 219 COVID-19, 1341 normal, and 1345 viral pneumonia chest X-ray (CXR) images. In the first update, we have increased the COVID-19 class to 1200 CXR images. In the 2nd update, we have increased the database to 3616 COVID-19 positive cases along with 10,192 Normal, 6012 Lung Opacity (Non-COVID lung infection), and 1345 Viral Pneumonia images and corresponding lung masks. We will continue to update this database as soon as we have new x-ray images for COVID-19 pneumonia patients.

Introducing paper: Can AI help in screening Viral and COVID-19 pneumonia?
VDD
Full name: Varied Drone Dataset for Semantic Segmentation

Semantic segmentation of drone images is critical for various aerial vision tasks as it provides essential seman- tic details to understand scenes on the ground. Ensuring high accuracy of semantic segmentation models for drones requires access to diverse, large-scale, and high-resolution datasets, which are often scarce in the field of aerial image processing. While existing datasets typically focus on urban scenes and are relatively small, our Varied Drone Dataset (VDD) addresses these limitations by offering a large-scale, densely labeled collection of 400 high-resolution images spanning 7 classes. This dataset features various scenes in urban, industrial, rural, and natural areas, captured from different camera angles and under diverse lighting conditions.

Introducing paper: VDD: Varied Drone Dataset for Semantic Segmentation
Integrated Drone Dataset for Semantic Segmentation
Full name: IDD

Semantic segmentation of drone images is critical for various aerial vision tasks as it provides essential semantic details to understand scenes on the ground. Ensuring high accuracy of semantic segmentation models for drones requires access to diverse, large-scale, and high-resolution datasets, which are often scarce in the field of aerial image processing. While existing datasets typically focus on urban scenes and are relatively small, our Varied Drone Dataset (VDD) addresses these limitations by offering a large-scale, densely labeled collection of 400 high-resolution images spanning 7 classes. This dataset features various scenes in urban, industrial, rural, and natural areas, captured from different camera angles and under diverse lighting conditions. We also make new annotations to UDD and UAVid, integrating them under VDD annotation standards, to create the Integrated Drone Dataset (IDD). It's expected that our dataset will generate considerable interest in drone image segmentation and serve as a foundation for other drone vision tasks.

Introducing paper: VDD: Varied Drone Dataset for Semantic Segmentation
ThermoScenes

Dataset of paired thermal and RGB images comprising ten diverse scenes—six indoor and four outdoor scenes— for 3D scene reconstruction and novel view synthesis (e.g. with NeRF).

Introducing paper: ThermoNeRF: Joint RGB and Thermal Novel View Synthesis for Building Facades using Multimodal Neural Radiance Fields