TFeat shallow convolutional patch descriptor

Code for the BMVC 2016 paper Learning local feature descriptors with triplets and shallow convolutional neural networks

Network description

We provide 4 variants of the TFeat descriptor trained with combinations of different loss functions, and with and without in-triplet anchor swap. For more details check the paper.

network	description
tfeat-ratio	ratio w/out anchor swap
tfeat-ratio*	ratio with anchor swap
tfeat-margin	margin w/out anchor swap
tfeat-margin*	margin with anchor swap

To download the networks run the get_nets.sh script

sh get_nets.sh

[New] Example usage - Tensorflow

Example on how to use and train the network using Tensorflow can be found here

Example usage - torch

Example on how to use the TFeat descriptor in Torch can be found here

Example usage - python

tfeat_demo.py shows how to use the TFeat descriptor using python and openCV.

To use TFeat to detect an object object_img.png in a video input_video.webm using feature point matching

python tfeat_demo.py nets/tfeat_liberty_margin_star.t7 input_video.webm object_img.png'

Real-time Matching demo

Real-time demo on using TFeat

More information

More information and the full training code can be found in the pnnet repository