vbalnt/tfeat
TFeat descriptor models for BMVC 2016 paper "Learning local feature descriptors with triplets and shallow convolutional neural networks"
TFeat helps computer vision engineers match features between different images. It takes image patches as input and outputs unique descriptors for each patch, which can then be used to find correspondences between images. This is ideal for tasks like image stitching, object recognition, or 3D reconstruction.
150 stars. No commits in the last 6 months.
Use this if you need to reliably identify and match specific visual points or areas across multiple images, even with variations in lighting or viewpoint.
Not ideal if your primary goal is general image classification or object detection rather than precise feature correspondence.
Stars
150
Forks
44
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 16, 2021
Commits (30d)
0
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