bityangke / deep-semantic-feature-correspondence-with-weakly-supervised-learning

semantic-correspondece

Deep-Semantic-Feature-Correspondence-with-weakly-supervised-learning

This is a project for solving "image semantic matching" by End-to-end Convolutional Neural Network with weakly-supervised learning. The main reference paper includes "Convolutional Neural Network Architecture for Geometric Matching"[1] in CVPR-2017, "End-to-end weakly-supervised semantic alignment"[2] in CVPR-2018 and "Neighbourhood Consensus Networks"[3] in NIPS-2018.

[1] I. Rocco, R. Arandjelovic and J. Sivic . Convolutional Neural Network Architecture for Geometric Matching. IEEE Conference on Computer Vision and Pattern Recognition (pp.39-48),2017

[2] I. Rocco, R. Arandjelovic and J. Sivic. End-to-end weakly-supervised semantic alignment.IEEE Conference on Computer Vision and Pattern Recognition,2018

[3] I. Rocco, M. Cimpoi, R. Arandjelović, A. Torii, T. Pajdla and J. Sivic. Neighbourhood Consensus Networks. In Proceedings of the 32nd Conference on Neural Information Processing Systems, 2018