AlexanderMelde/SPHAR-Dataset
Surveillance Perspective Human Action Recognition Dataset: 7759 Videos from 14 Action Classes, aggregated from multiple sources, all cropped spatio-temporally and filmed from a surveillance-camera like position.
SPHAR is a collection of 7,759 video clips designed for training and evaluating automated systems that identify human actions from surveillance footage. It takes raw video clips as input and provides categorized videos showing 14 distinct actions (like falling, running, or stealing) all from a surveillance camera's point of view. This dataset is for researchers and engineers developing AI for public safety, security monitoring, or behavior analysis in environments with fixed camera setups.
118 stars. No commits in the last 6 months.
Use this if you are building or testing a computer vision system to automatically recognize human actions from video recorded by surveillance cameras.
Not ideal if your project involves analyzing human actions from different camera angles (e.g., first-person, drone, or body-worn cameras) or if you need highly precise spatial and temporal cropping for every single video.
Stars
118
Forks
23
Language
Python
License
—
Category
Last pushed
Apr 02, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/AlexanderMelde/SPHAR-Dataset"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
quic/sense
Enhance your application with the ability to see and interact with humans using any RGB camera.
CV-ZMH/human-action-recognition
Multi Person Skeleton Based Action Recognition and Tracking
Event-AHU/HARDVS
[AAAI-2024] HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors
mmact19/2019
MMAct: A Large-Scale Dataset for Cross Modal Learning on Human Action Understanding
yujmo/CZU_MHAD
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10...