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Rethinking Portrait Matting with Privacy Preserving
Recently, there has been an increasing concern about the privacy issue raised by identifiable information in machine learning. However, previous portrait matting methods were all based on identifiable images. To fill the gap, we present P3M-10k, which is the first large-scale anonymized benchmark fo...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199740/ https://www.ncbi.nlm.nih.gov/pubmed/37363293 http://dx.doi.org/10.1007/s11263-023-01797-8 |