Browse State-of-the-Art › Mirror Detection
Mirror Detection
8 papers with code · 0 benchmarks · 2 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
8 shown of 8 papers with code (14 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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1 Jan 2025 1 repository listedTo effectively exploit this unlabeled dataset, we propose the first semi-supervised framework (namely an iterative data engine) consisting of four steps: (1) mirror detection model training, (2) pseudo label prediction,…
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26 Dec 2024 1 repository listedAs the successor to the Segment Anything Model (SAM), the Segment Anything Model 2 (SAM2) not only improves performance in image segmentation but also extends its capabilities to video segmentation.
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16 Aug 2024 1 repository listed Syntology ran 5 of 9 samples · 4 unverifiedImage segmentation plays an important role in vision understanding.
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10 Jul 2024 1 repository listedHowever, to ensure that the candidate is indeed a mirror (not a picture or a window), we often need to observe more frames for a global view.
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1 Jan 2024 1 repository listedNext we observed that the motions between the inside and outside of the mirror are often inconsistent.
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28 Nov 2022 1 repository listedWe present HetNet (Multi-level \textbf{Het}erogeneous \textbf{Net}work), a highly efficient mirror detection network.
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13 Jul 2022 1 repository listedMirror detection aims to identify the mirror regions in the given input image.
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24 Mar 2021 1 repository listedHowever, these methods usually encounter boundary-related imbalance problem, leading to limited generation capability.
Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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