@inproceedings{malkin2020mining,
author = {Malkin, Kolya and Ortiz, Anthony and Robinson, Caleb and Jojic, Nebojsa},
title = {Mining self-similarity: Label super-resolution with epitomic representations},
booktitle = {16th European Conference Computer Vision (ECCV 2020)},
year = {2020},
month = {August},
abstract = {We show that simple patch-based models, such as epitomes, can have superior performance to the current state of the art in semantic segmentation and label super-resolution, which uses deep convolutional neural networks. We derive a new training algorithm for epitomes which allows, for the first time, learning from very large data sets and derive a label super-resolution algorithm as a statistical inference algorithm over epitomic representations. We illustrate our methods on land cover mapping and medical image analysis tasks.},
url = {http://approjects.co.za/?big=en-us/research/publication/mining-self-similarity-label-super-resolution-with-epitomic-representations/},
}