dsshim0125/SwinDepth
"SwinDepth: Unsupervised Depth Estimation using Monocular Sequences via Swin Transformer and Densely Cascaded Network" (ICRA 2023)
This project helps convert a sequence of standard camera images into detailed depth maps, showing how far away objects are from the camera. You provide a video sequence (or a folder of images), and it generates corresponding depth maps. This is useful for researchers and engineers working on autonomous vehicles, robotics, or 3D scene understanding.
No commits in the last 6 months.
Use this if you need to quickly estimate the depth of objects in a scene from monocular video footage without requiring specialized depth sensors.
Not ideal if you require real-time depth sensing for dynamic environments or need extremely high-precision depth measurements for industrial applications.
Stars
39
Forks
1
Language
Python
License
MIT
Category
Last pushed
Mar 08, 2023
Commits (30d)
0
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