ShuweiShao/AF-SfMLearner
[MedIA2022 & ICRA2021] Self-Supervised Monocular Depth and Ego-Motion Estimation in Endoscopy: Appearance Flow to the Rescue
This project helps medical imaging researchers or roboticists working with endoscopy videos. It takes standard endoscopic video footage and automatically generates detailed depth maps, allowing you to understand the 3D structure of internal anatomy, along with estimations of camera movement and 3D reconstructions. This is invaluable for surgical navigation, robotic assistance, or quantitative analysis of endoscopic procedures.
138 stars. No commits in the last 6 months.
Use this if you need to extract precise 3D depth information and camera motion from monocular (single-camera) endoscopic video sequences without relying on complex, multi-camera setups or external sensors.
Not ideal if your primary goal is general object detection or classification in medical images, or if you are working with non-endoscopic medical imaging modalities like MRI or CT scans.
Stars
138
Forks
19
Language
Python
License
MIT
Category
Last pushed
Jul 02, 2024
Commits (30d)
0
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