上流社会 发表于 2025-3-30 11:07:31

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开始发作 发表于 2025-3-30 16:13:07

https://doi.org/10.1007/978-3-031-20325-1they usually suffer from the over-expansion due to an absence of guidelines on when to stop erasing. We experimentally verify that the over-expansion is due to rigid classification, and metric learning can be a flexible remedy for it. AEFT is devised to learn the concept of erasing with the triplet

GOUGE 发表于 2025-3-30 16:56:05

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补角 发表于 2025-3-31 00:03:04

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BARGE 发表于 2025-3-31 01:27:00

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organic-matrix 发表于 2025-3-31 08:22:53

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coalition 发表于 2025-3-31 11:05:36

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和平 发表于 2025-3-31 13:21:46

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松紧带 发表于 2025-3-31 20:17:23

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Essential 发表于 2025-4-1 00:09:38

,Adaptive Spatial-BCE Loss for Weakly Supervised Semantic Segmentation,strategy to adaptively generate thresholds to divide the foreground and background. Benefiting from high-quality initial pseudo-labels by Spatial-BCE Loss, our method also reduce the reliance on post-processing, thereby simplifying the pipeline of WSSS. Our method is validated on the PASCAL VOC 2012
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查看完整版本: Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app