Tackling background ambiguities in multi-class few-shot point cloud semantic segmentation

Tackling background ambiguities in multi-class few-shot point cloud semantic segmentation

Few-shot point cloud semantic segmentation learns to segment novel classes with scarce labeled samples. Within an episode, a novel target class is defined by a few support samples with corresponding binary masks, where only the points of this class are labeled as foreground and others are regarded a...

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書目詳細資料
Main Authors:	Lai, Lvlong, Chen, Jian, Zhang, Chi, Zhang, Zehong, Lin, Guosheng, Wu, Qingyao
其他作者:	School of Computer Science and Engineering
格式:	Article
語言:	English
出版:	2022
主題:	Engineering::Computer science and engineering Few-Shot Point Cloud
在線閱讀:	https://hdl.handle.net/10356/163370
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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