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Rethinking interactive image segmentation: Feature space annotation

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Autor(es):
Bragantini, Jordao ; Falcao, Alexandre X. ; Najman, Laurent
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: PATTERN RECOGNITION; v. 131, p. 12-pg., 2022-07-13.
Resumo

Despite the progress of interactive image segmentation methods, high-quality pixel-level annotation is still time-consuming and laborious - a bottleneck for several deep learning applications. We take a step back to propose interactive and simultaneous segment annotation from multiple images guided by feature space projection. This strategy is in stark contrast to existing interactive segmentation methodologies, which perform annotation in the image domain. We show that feature space annotation achieves com-petitive results with state-of-the-art methods in foreground segmentation datasets: iCoSeg, DAVIS, and Rooftop. Moreover, in the semantic segmentation context, it achieves 91.5% accuracy in the Cityscapes dataset, being 74.75 times faster than the original annotation procedure. Further, our contribution sheds light on a novel direction for interactive image annotation that can be integrated with existing method-ologies. The supplementary material presents video demonstrations. Code available at https://github.com/ LIDS- UNICAMP/rethinking- interactive- image-segmentation . (c) 2022 Elsevier Ltd. All rights reserved. (AU)

Processo FAPESP: 19/21734-9 - Co-segmentação interativa com aprendizado de projeção
Beneficiário:Jordão Okuma Barbosa Ferraz Bragantini
Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Iniciação Científica
Processo FAPESP: 14/12236-1 - AnImaLS: Anotação de Imagem em Larga Escala: o que máquinas e especialistas podem aprender interagindo?
Beneficiário:Alexandre Xavier Falcão
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 19/11349-0 - Segmentação de imagens baseada em dynamic-trees e neural networks
Beneficiário:Jordão Okuma Barbosa Ferraz Bragantini
Modalidade de apoio: Bolsas no Brasil - Iniciação Científica