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jzbontar avatar

jzbontar/mc-cnn

0
View on GitHub↗
726 stars·226 forks·Cuda·BSD-2-Clause·15 views

Mc Cnn

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

Features

  • Computer Vision Frameworks - Convolutional neural network architecture for stereo matching tasks.
  • Machine Learning MVS - Deep learning architecture for patch-based stereo matching.
  • Terrain and 3D Reconstruction - Stereo matching using convolutional neural networks.
  • Terrain and Elevation - Stereo matching using convolutional neural networks.

Star history

Star history chart for jzbontar/mc-cnnStar history chart for jzbontar/mc-cnn

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Mc Cnn

These projects share indexed features with Mc Cnn. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • giswqs/lidargiswqs avatar

    giswqs/lidar

    297View on GitHub↗

    A Python package for delineating nested surface depressions from digital elevation data.

    Python
    View on GitHub↗297
  • intelrealsense/librealsenseI

    IntelRealSense/librealsense

    0View on GitHub↗
    View on GitHub↗0
  • cmla/s2pcmla avatar

    cmla/s2p

    259View on GitHub↗

    S2P is a Python library and command line tool that implements a stereo pipeline which produces elevation models from images taken by high resolution optical satellites such as Pléiades, WorldView, QuickBird, Spot or Ikonos. It generates 3D point clouds and digital surface models from stereo…

    Python
    View on GitHub↗259
  • miss3d/s2pMISS3D avatar

    MISS3D/s2p

    148View on GitHub↗

    Warning: this repository is not maintained, please use https://github.com/centreborelli/s2p instead.

    C
    View on GitHub↗148
Compare all 30 related projects→

Frequently asked questions

What does jzbontar/mc-cnn do?

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

What are the main features of jzbontar/mc-cnn?

The main features of jzbontar/mc-cnn are: Computer Vision Frameworks, Machine Learning MVS, Terrain and 3D Reconstruction, Terrain and Elevation.

Which projects share features with jzbontar/mc-cnn?

Projects with overlapping indexed features include: intelrealsense/librealsense. mrharicot/monodepth — Tensorflow implementation of unsupervised single image depth prediction using a convolutional neural network. cmla/s2p — S2P is a Python library and command line tool that implements a stereo pipeline which produces elevation models from… giswqs/lidar — A Python package for delineating nested surface depressions from digital elevation data. miss3d/s2p — Warning: this repository is not maintained, please use https://github.com/centreborelli/s2p instead. msracver/deformable-convnets — Deformable-ConvNets is a computer vision framework and a collection of neural network components designed to implement…