NeurAI-Lab/MT-SfMLearner
Official code for 'Transformers in Unsupervised Structure-from-Motion' and 'Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera Intrinsics'
This project helps computer vision researchers analyze video sequences to understand the 3D structure of scenes and objects. It takes video footage as input and outputs detailed depth maps for each frame, even if the camera's internal settings are unknown. This is ideal for researchers in robotics, autonomous driving, or 3D reconstruction who need to extract spatial information from videos.
No commits in the last 6 months.
Use this if you need to determine the precise distance of objects from a camera in video footage without needing to calibrate the camera.
Not ideal if you require real-time processing on embedded devices or have static images rather than video sequences for analysis.
Stars
14
Forks
2
Language
Python
License
MIT
Category
Last pushed
Nov 12, 2023
Commits (30d)
0
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