lilygeorgescu/AED-SSMTL
Anomaly Detection in Video via Self-Supervised and Multi-Task Learning
This project helps security and operations teams automatically detect unusual events in surveillance video footage. It takes raw video streams as input and identifies specific moments or objects behaving abnormally, flagging them for review. Security analysts, operations managers, and public safety personnel are the primary users who would benefit from this early warning system.
No commits in the last 6 months.
Use this if you need to automatically identify suspicious or unusual activities in surveillance video, such as someone moving in a prohibited direction, objects appearing irregularly, or unexpected behaviors in crowded scenes.
Not ideal if you need to detect anomalies in data types other than video, or if you require real-time, instantaneous alerts without any processing delay.
Stars
60
Forks
2
Language
TeX
License
—
Category
Last pushed
Apr 12, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lilygeorgescu/AED-SSMTL"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
unit8co/darts
A python library for user-friendly forecasting and anomaly detection on time series.
elki-project/elki
ELKI Data Mining Toolkit
raphaelvallat/antropy
AntroPy: entropy and complexity of (EEG) time-series in Python
Minqi824/ADBench
Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.