Model description

The SuperGlue network is a Graph Neural Network combined with an Optimal Matching layer that is trained to perform matching on two sets of sparse image features.
SuperGlue is built on top of SuperPoint model which consists of detecting the most interesting keypoints in an image. With the keypoints of two different images, SuperGlue proceeds to the matching.

I noticed there was no image matching models implemented in transformers library so I propose this first one. I extensively used it in other activities and am new to transformers git contributions, so I am willing to implement it myself as a first contribution.

Open source status

• The model implementation is available
• The model weights are available

Provide useful links for the implementation

SuperPoint and SuperGlue code and weights are available at https://github.com/magicleap/SuperGluePretrainedNetwork
The original paper of SuperPoint : https://arxiv.org/abs/1712.07629
The original paper of SuperGlue : https://arxiv.org/abs/1911.11763