Give Machines the Power to See People.

This isn’t just a dataset — it’s a foundation for building the future of human-aware technology. Carefully crafted and annotated with precision, the People Detection dataset enables AI systems to recognize and understand human presence in dynamic, real-world environments.

Whether you’re building smart surveillance, autonomous vehicles, crowd analytics, or next-gen robotics, this dataset gives your model the eyes it needs.

What Makes This Dataset Different?

• Real-World Images – Diverse environments, realistic lighting, and real human motion
• High-Quality Annotations – Every person labeled with clean YOLO-format bounding boxes
• Plug-and-Play – Comes with pre-split training, validation, and test sets — no extra prep needed
• Speed-Optimized – Perfect for real-time object detection applications

Built for Visionaries

• Detect people instantly — in cities, offices, or crowds
• Build systems that respond to human presence
• Train intelligent agents to navigate human spaces safely and smartly

Created using Roboflow. Optimized for clarity, performance, and scale. Source Dataset on Roboflow →

This is more than a dataset. It’s a step toward a smarter world — One where machines can understand people.

A synthetic dataset for visual fallen people detection comprising images extracted from the highly photo-realistic video game Grand Theft Auto V developed by Rockstar North. Each image is labeled by the game engine providing bounding boxes and statuses (fallen or non-fallen) of people present in the scene. The dataset comprises 6,071 synthetic images depicting 7,456 fallen and 26,125 non-fallen pedestrian instances in various looks, camera positions, background scenes, lightning, and occlusion conditions.

Number of people who are undernourished in World was reported at 722000000 in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Number of people who are undernourished - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Dataset

This dataset was created by EbruKaranci

Contents

Dataset

This dataset was created by JR

Contents

Researchers in R&D (per million people) in World was reported at 1516 in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Researchers in R&D (per million people) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

This dataset is about book subjects. It has 1 row and is filtered where the books is World-wide issues : people, resources and the environment. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Object recognition predominately still relies on many high-quality training examples per object category. In contrast, learning new objects from only a few examples could enable many impactful applications from robotics to user personalization. Most few-shot learning research, however, has been driven by benchmark datasets that lack the high variation that these applications will face when deployed in the real-world. To close this gap, we present the ORBIT dataset, grounded in a real-world application of teachable object recognizers for people who are blind/low vision. We provide a full, unfiltered dataset of 4,733 videos of 588 objects recorded by 97 people who are blind/low-vision on their mobile phones, and a benchmark dataset of 3,822 videos of 486 objects collected by 77 collectors. The code for loading the dataset, computing all benchmark metrics, and running the baseline models is available at https://github.com/microsoft/ORBIT-DatasetThis version comprises several zip files:- train, validation, test: benchmark dataset, organised by collector, with raw videos split into static individual frames in jpg format at 30FPS- other: data not in the benchmark set, organised by collector, with raw videos split into static individual frames in jpg format at 30FPS (please note that the train, validation, test, and other files make up the unfiltered dataset)- *_224: as for the benchmark, but static individual frames are scaled down to 224 pixels.- *_unfiltered_videos: full unfiltered dataset, organised by collector, in mp4 format.

Trends in People fully vaccinated against Covid. The latest data for over 100 countries around the world.

This dataset is about books. It has 1 row and is filtered where the book is World-wide issues : people, resources and the environment. It features 7 columns including author, publication date, language, and book publisher.

People practicing open defecation (% of population) in World was reported at 5.3552 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - People practicing open defecation (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

Content

This dataset contains the population and density related info per (Country, State). The Country and State names are compatible with the COVID-19 weekly forecasting dataset.

Acknowledgements

https://www.kaggle.com/koryto/countryinfo

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

People practicing open defecation, urban (% of urban population) in World was reported at 0.81293 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - People practicing open defecation, urban - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

Welcome to the Human Capital Project (HCP), a global effort to accelerate more and better investments in people for greater equity and economic growth. In a post-COVID-19 pandemic world, it's even more important to understand why countries should invest in human capital (HC) and protect hard-won gains from being eroded. Find out why the World Bank, countries, and partners are coming together to close the massive HC gap in the world. Check out the Human Capital Network Fact Sheet, updated 2020 Human Capital Index, our videos, visualizations, frequently-asked-questions, and more.

obtaining large

RealVAD: A Real-world Dataset for Voice Activity Detection

The task of automatically detecting “Who is Speaking and When” is broadly named as Voice Activity Detection (VAD). Automatic VAD is a very important task and also the foundation of several domains, e.g., human-human, human-computer/ robot/ virtual-agent interaction analyses, and industrial applications.

RealVAD dataset is constructed from a YouTube video composed of a panel discussion lasting approx. 83 minutes. The audio is available from a single channel. There is one static camera capturing all panelists, the moderator and audiences.

Particular aspects of RealVAD dataset are:

• It is composed of panelists with different nationalities (British, Dutch, French, German, Italian, American, Mexican, Columbian, Thai). This aspect allows studying the effect of ethnic origin variety to the automatic VAD.
• There is a gender balance such that there are four female and five male panelists.
• The panelists are sitting in two rows and they can be gazing audience, other panelists, their laptop, the moderator or anywhere in the room while speaking or not-speaking. Therefore, they were captured not only from frontal-view but also from side-view varying based on their instant posture and head orientation.
• The panelists are moving freely and are doing various spontaneous actions (e.g., drinking water, checking their cell phone, using their laptop, etc.), resulting in different postures.
• The panelists’ body parts are sometimes partially occluded by their/other's body part or belongings (e.g., laptop).
• There are also natural changes of illumination and shadow rising on the wall behind the panelists in the back row.
• Especially, for the panelists sitting in the front row, there is sometimes background motion occurring when the person(s) behind them moves.

The annotations includes:

• The upper body detection of nine panelists in bounding box form.
• Associated VAD ground-truth (speaking, not-speaking) for nine panelists.
• Acoustic features extracted from the video: MFCC and raw filterbank energies.

All info regarding the annotations are given in the ReadMe.txt and Acoustic Features README.txt files.

When using this dataset for your research, please cite the following paper in your publication:

1. C. Beyan, M. Shahid and V. Murino, "RealVAD: A Real-world Dataset and A Method for Voice Activity Detection by Body Motion Analysis", in IEEE Transactions on Multimedia, 2020.

Over the past 23 years, there were constantly more men than women living on the planet. Of the 8.06 billion people living on the Earth in 2023, 4.05 billion were men and 4.01 billion were women. One-quarter of the world's total population in 2024 was below 15 years.

This update to the Human Footprint (HFP) provides a measure of the direct and indirect human pressures on the environment globally in years 2000, 2005, 2010, and 2013. Per the orinal Human Footprint, this dataset is derived from remotely-sensed and bottom-up survey information compiled on eight measured variables. This represents not only the most current information of its type, but also the first temporally-consistent set of Human Footprint maps. Data on human pressures were acquired or developed for: 1) built environments, 2) population density, 3) electric infrastructure, 4) crop lands, 5) pasture lands, 6) roads, 7) railways, and 8) navigable waterways. This update incorporates updated and higher resolution population, nightlights, pasture, road, and railway input datasets. The Human Footprint maps find a range of uses as proxies for human disturbance of natural systems and can provide an increased understanding of the human pressures that drive macro-ecological patterns, as well as for tracking environmental change and informing conservation science and application. HFP values range from 0 (no human impact) to 50 (heavily human impacted).

See: Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11.

This dataset can be downloaded uniquly from UN Biodiversity Lab.
Updated data is made available only to FIP pilot countires at present - rasters are clipped to other FIP data extents.

The geographic distribution of human population is key to understanding the effects of humans on the natural world and how natural events such as storms, earthquakes, and other natural phenomenon affect humans. Dataset SummaryThis layer was created with a model that combines imagery, road intersection density, populated places, and urban foot prints to create a likelihood surface. The likelihood surface is then used to create a raster of population with a cell size of 0.00221 degrees (approximately 250 meters).The population raster is created usingDasymetriccartographic methods to allocate the population values in over 1.6 million census polygons covering the world.The population of each polygon was normalized to the 2013 United Nations population estimates by country.Each cell in this layer has an integer value depicting the number of people that are likely to reside in that cell. Tabulations based on these values should result in population totals that more accurately reflect the population of areas of several square kilometers.This layer has global coverage and was published by Esri in 2014.More information about this layer is available:Building the Most Detailed Population Map in the World