Skip to content

Latest commit

 

History

History
58 lines (41 loc) · 2.43 KB

README.md

File metadata and controls

58 lines (41 loc) · 2.43 KB
Raw

Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation

This repository contains code and models for the method described in:

Golnaz Ghiasi, Charless C. Fowlkes, "Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation", ECCV 2016

The code is written in Matlab, it uses Matconvnet library and is based on the following repository:

This code is tested on Linux using matconvnet v1.0-beta20 and cuDNN 5

Testing pre-trained models

Download pre-trained models and extract it into models directory.

Testing pre-trained model on PASCAL VOC validation data

Specify matconvnet path in "LRRTestOnPascal.m" and execute it.

Testing pre-trained model on Cityscape validation data

Download "gtFine_trainvaltest.zip" and "leftImg8bit_trainvaltest.zip" from Cityscapes dataset website, unzip them. Specify their path ("opts.dataDir") and matconvnet path ("path_to_matconvnet") in "LRRTestOnCityScape.m" and execute it.

Training LRR on PASCAL VOC training data

Specify matconvnet path in "LRR4xTrainVGG16Pascal.m" and execute it.

Issues, Questions, etc

Please contact "gghiasi @ ics.uci.edu"

Copyright (C) 2016 Golnaz Ghiasi, Charless C. Fowlkes

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.