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COMAL: compositional multi-scale feature enhanced learning for crowd counting
Accurately modeling the crowd’s head scale variations is an effective way to improve the counting accuracy of the crowd counting methods. Most counting networks apply a multi-branch network structure to obtain different scales of head features. Although they have achieved promising results, they do...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914450/ https://www.ncbi.nlm.nih.gov/pubmed/35291715 http://dx.doi.org/10.1007/s11042-022-12249-9 |