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A systematic review on open-set segmentation

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Author(s):
Nunes, Ian ; Laranjeira, Camila ; Oliveira, Hugo ; dos Santos, Jefersson A.
Total Authors: 4
Document type: Journal article
Source: COMPUTERS & GRAPHICS-UK; v. 115, p. 13-pg., 2023-10-01.
Abstract

Open-set semantic segmentation remains yet a challenging task, not only due to the inherent challenges of pixel-wise classification but also the precise segmentation of categories not seen during training. The pursuit of that task is rapidly growing in the Computer Vision community, urging the need to organize the literature. In this paper, we extend our previous work by conducting a more comprehensive systematic mapping of the open-set segmentation literature between January 2001 and January 2023 and proposing a novel taxonomy. Our goal is to provide a broad understanding of current trends for the open-set semantic segmentation (OSS) task defined by existing approaches that may influence future methods. By characterizing methodologies in terms of open-set identification strategies, data inputs, and other relevant aspects, we present a structured view of how researchers are advancing in the field of open-set semantic segmentation. To the best of the authors' knowledge, this is the first systematic review of OSS methods. Moreover, we apply the proposed taxonomy to selected methods for open-set recognition, outlining important similarities and differences of such a closely related field. (c) 2023 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 17/50236-1 - Spatio temporal analysis of pediatric magnetic resonance images
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Regular Research Grants
FAPESP's process: 20/06744-5 - Deep learning and intermediate representations for pediatric image analysis
Grantee:Hugo Neves de Oliveira
Support Opportunities: Scholarships in Brazil - Post-Doctoral