SfMLearner and ThermalSfMLearner-MS
About SfMLearner
tinghuiz/SfMLearner
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
This project helps robotics engineers and autonomous vehicle developers understand their environment by estimating scene depth and camera motion from standard video. It takes a monocular video sequence as input and outputs a depth map for each frame, showing how far away objects are, and the camera's movement between frames. This is useful for building self-navigating systems.
About ThermalSfMLearner-MS
UkcheolShin/ThermalSfMLearner-MS
Official implementation of the paper "Self-supervised Depth and Ego-motion Estimation for Monocular Thermal Video using Multi-spectral Consistency Loss"
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.
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