Methods › General › Normalization › SyncBN
Synchronized Batch Normalization
SyncBN
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Synchronized Batch Normalization (SyncBN) is a type of batch normalization used for multi-GPU training. Standard batch normalization only normalizes the data within each device (GPU). SyncBN normalizes the input within the whole mini-batch.
Papers archive 2025-07-28
5 shown of 5, 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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1st Place Solution for ICDAR 2021 Competition on Mathematical Formula Detection 12 Jul 2021 · 1 repository · arXiv:2107.05534
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An Efficient and Scalable Deep Learning Approach for Road Damage Detection 18 Nov 2020 · 2 repositories · arXiv:2011.09577
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Grid R-CNN 29 Nov 2018 · 2 repositories · arXiv:1811.12030Syntology ran 0 of 3 samples · 3 unverified
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PSANet: Point-wise Spatial Attention Network for Scene Parsing 1 Sep 2018 · 4 repositories
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Context Encoding for Semantic Segmentation 23 Mar 2018 · 12 repositories · arXiv:1803.08904Syntology ran 1 of 8 samples · 7 unverified · 7 pointer-only (licence)
Tasks archive 2025-07-28
16 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
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections