UkcheolShin/ThermalSfMLearner-MS

Official implementation of the paper "Self-supervised Depth and Ego-motion Estimation for Monocular Thermal Video using Multi-spectral Consistency Loss"

38
/ 100
Emerging

This project helps operations engineers, security personnel, or emergency responders analyze thermal video footage. It takes a single stream of thermal video and, without needing additional sensors or prior mapping, estimates how far away objects are and how the camera itself is moving. This allows for detailed scene understanding in challenging environments like nighttime or smoke.

No commits in the last 6 months.

Use this if you need to understand depth and camera movement from monocular thermal video, especially when traditional visual methods are hindered by low light or obscured visibility.

Not ideal if your primary data source is standard visible light video, or if you require real-time processing on embedded systems without significant computational resources.

thermal-imaging robotics-navigation autonomous-systems surveillance search-and-rescue
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 15 / 25

How are scores calculated?

Stars

40

Forks

7

Language

Python

License

GPL-3.0

Last pushed

Jul 19, 2022

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/UkcheolShin/ThermalSfMLearner-MS"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.