This is the Linux app named Consistent Depth whose latest release can be downloaded as consistent_depthsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Consistent Depth
OPIS
Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. This approach achieves improved geometric consistency and visual stability compared to prior monocular reconstruction methods. The project can process challenging hand-held video footage, including those with moderate dynamic motion, making it practical for real-world usage.
Funkcjonalności
- Reconstructs dense, geometrically consistent depth from monocular videos
- Integrates structure-from-motion with deep learning-based depth priors
- Supports test-time fine-tuning for video-specific geometric constraints
- Provides higher accuracy and consistency than classical monocular reconstruction methods
- Compatible with dynamic hand-held videos and real-world camera motion
- Enables scene reconstruction and video visual effects through improved depth estimation
Język programowania
Python, powłoka uniksowa
Kategorie
This is an application that can also be fetched from https://sourceforge.net/projects/consistent-depth.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
