Showing 4 open source projects for "visual python"

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    VMZ (Video Model Zoo)

    VMZ (Video Model Zoo)

    VMZ: Model Zoo for Video Modeling

    The codebase was designed to help researchers and practitioners quickly reproduce FAIR’s results and leverage robust pre-trained backbones for downstream tasks. It also integrates Gradient Blending, an audio-visual modeling method that fuses modalities effectively (available in the Caffe2 implementation). Although VMZ is now archived and no longer actively maintained, it remains a valuable reference for understanding early large-scale video model training, transfer learning, and multimodal...
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  • 2
    VGGSfM

    VGGSfM

    VGGSfM: Visual Geometry Grounded Deep Structure From Motion

    VGGSfM is an advanced structure-from-motion (SfM) framework jointly developed by Meta AI Research (GenAI) and the University of Oxford’s Visual Geometry Group (VGG). It reconstructs 3D geometry, dense depth, and camera poses directly from unordered or sequential images and videos. The system combines learned feature matching and geometric optimization to generate high-quality camera calibrations, sparse/dense point clouds, and depth maps in standard COLMAP format. Version 2.0 adds support...
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  • 3

    openSkyMatch

    Matches OpenScience Observatories images with astronomical catalogs

    openSkyMatch is a collection of Linux shell and Python scripts designed for the OpenScience Observatories program. It automates the identification and matching of detected celestial objects in locally captured FITS images with entries in large-scale sky catalogs, notably Pan-STARRS1 DR2 (II/389/ps1_dr2). The toolkit supports data preprocessing, coordinate correlation, and catalog-based validation of astronomical detections. All tools are open-source and optimized for reproducibility and...
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  • 4
    Consistent Depth

    Consistent Depth

    We estimate dense, flicker-free, geometrically consistent depth

    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...
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