TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation

By Vladimir Iglovikov, Alexey Shvets

Introduction

TernausNet is a modification of the celebrated UNet architecture that is widely used for binary Image Segmentation. For more details, please refer to our arXiv paper.

(Network architecure)

Pre-trained encoder speeds up convergence even on the datasets with a different semantic features. Above curve shows validation Jaccard Index (IOU) as a function of epochs for Aerial Imagery

This architecture was a part of the winning solutiuon (1st out of 735 teams) in the Carvana Image Masking Challenge.

Citing TernausNet

Please cite TernausNet in your publications if it helps your research:

@ARTICLE{2018arXiv180105746I,
   author = {Iglovikov, V. and Shvets, A.},
    title = "{TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation}",
  journal = {ArXiv e-prints},
archivePrefix = "arXiv",
   eprint = {1801.05746}, 
     year = 2018,
    month = jan}