CASENet: Deep Category-Aware Semantic Edge Detection

<p><strong>Introduction</strong></p> <p>This dataset includes initial and trained model weights (caffemodel files) for SBD/Cityscapes datasets which is used in our CASENet software available (<a href="https://github.com/merlresearch/CASENet">https://github.com/merlresearch/CASENet</a>).</p> <p><strong>Citation</strong></p> <p>If you use the data, please cite the following <a href="https://www.merl.com/publications/TR2017-100">TR2017-100</a>:</p> <pre><code>@inproceedings{Yu2017jul, author = {Yu, Zhiding and Feng, Chen and Liu, Ming-Yu and Ramalingam, Srikumar}, title = {CASENet: Deep Category-Aware Semantic Edge Detection}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = 2017, month = jul, doi = {10.1109/CVPR.2017.191}, url = {https://www.merl.com/publications/TR2017-100} }</code></pre> <p>Copyright and License<br> The CASENet dataset is released under<a href="https://creativecommons.org/licenses/by-sa/4.0/"> CC-BY-SA-4.0 license</a>.</p> <p><br> All data:</p> <pre><code>Created by Mitsubishi Electric Research Laboratories (MERL), 2017, 2023 SPDX-License-Identifier: CC-BY-SA-4.0</code></pre> <p><br> &nbsp;</p>