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Introduction This dataset includes initial and trained model weights (caffemodel files) for SBD/Cityscapes datasets which is used in our CASENet software available (https://github.com/merlresearch/CASENet). Citation If you use the data, please cite the following TR2017-100: @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} } Copyright and License The CASENet dataset is released under CC-BY-SA-4.0 license. All data: Created by Mitsubishi Electric Research Laboratories (MERL), 2017, 2023 SPDX-License-Identifier: CC-BY-SA-4.0
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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