<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>Camouflaged Instance Segmentation In-the-Wild: Dataset, Method, and Benchmark Suite</dc:title><dc:creator>Le, Trung-Nghia; Cao, Yubo; Nguyen, Tan-Cong; Le, Minh-Quan; Nguyen, Khanh-Duy; Do, Thanh-Toan; Tran, Minh-Triet; Nguyen, Tam V.</dc:creator><dc:corporate_author/><dc:editor/><dc:description/><dc:publisher/><dc:date>2022-01-01</dc:date><dc:nsf_par_id>10330096</dc:nsf_par_id><dc:journal_name>IEEE Transactions on Image Processing</dc:journal_name><dc:journal_volume>31</dc:journal_volume><dc:journal_issue/><dc:page_range_or_elocation>287 to 300</dc:page_range_or_elocation><dc:issn>1057-7149</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1109/TIP.2021.3130490</dc:doi><dcq:identifierAwardId>2025234</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>