Methods › Computer Vision › Object Detection Models › U2-Net
U2-Net
Introduced by Xuebin Qin et al. in U²-Net: Going Deeper with Nested U-Structure for Salient Object Detection
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
U2-Net is a two-level nested U-structure architecture that is designed for salient object detection (SOD). The architecture allows the network to go deeper, attain high resolution, without significantly increasing the memory and computation cost. This is achieved by a nested U-structure: on the bottom level, with a novel ReSidual U-block (RSU) module, which is able to extract intra-stage multi-scale features without degrading the feature map resolution; on the top level, there is a U-Net like structure, in which each stage is filled by a RSU block.
Papers archive 2025-07-28
3 shown of 3, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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MATT-GS: Masked Attention-based 3DGS for Robot Perception and Object Detection 25 Mar 2025 · 0 repositories · arXiv:2503.19330
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SKDCGN: Source-free Knowledge Distillation of Counterfactual Generative Networks using cGANs 8 Aug 2022 · 1 repository · arXiv:2208.04226
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U²-Net: Going Deeper with Nested U-Structure for Salient Object Detection 18 May 2020 · 29 repositories · arXiv:2005.09007Syntology ran 4 of 42 samples · 38 unverified · 2 pointer-only (licence)
Tasks archive 2025-07-28
15 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
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Categories archive 2025-07-28
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