Copyright Pohang University of Science and Technology. All rights reserved. Contact persons: Hyeonowo Noh (hyeonwoonoh_ postech.ac.kr) This software is being made available for individual research use only. Any commercial use or redistribution of this software requires a license from the Pohang University of Science and Technology. You may use this work subject to the following conditions: 1. This work is provided "as is" by the copyright holder, with absolutely no warranties of correctness, fitness, intellectual property ownership, or anything else whatsoever. You use the work entirely at your own risk. The copyright holder will not be liable for any legal damages whatsoever connected with the use of this work. 2. The copyright holder retain all copyright to the work. All copies of the work and all works derived from it must contain (1) this copyright notice, and (2) additional notices describing the content, dates and copyright holder of modifications or additions made to the work, if any, including distribution and use conditions and intellectual property claims. Derived works must be clearly distinguished from the original work, both by name and by the prominent inclusion of explicit descriptions of overlaps and differences. 3. The names and trademarks of the copyright holder may not be used in advertising or publicity related to this work without specific prior written permission. 4. In return for the free use of this work, you are requested, but not legally required, to do the following: * If you become aware of factors that may significantly affect other users of the work, for example major bugs or deficiencies or possible intellectual property issues, you are requested to report them to the copyright holder, if possible including redistributable fixes or workarounds. * If you use the work in scientific research or as part of a larger software system, you are requested to cite the use in any related publications or technical documentation. The work is based upon: Hyeonwoo Noh, Seunghoon Hong, Bohyung Han. Learning Deconvolution Network for Semantic Segmentation arXiv:1505.04366, 2015. @article{noh2015learning, title={Learning Deconvolution Network for Semantic Segmentation}, author={Noh, Hyeonwoo and Hong, Seunghoon and Han, Bohyung}, journal={arXiv preprint arXiv:1505.04366}, year={2015} } This copyright notice must be retained with all copies of the software, including any modified or derived versions.