Codesota · Benchmark · u-diads-bibHome/Leaderboards/Vision & Documents/Document Layout Analysis/u-diads-bib
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u-diads-bib.

u-diads-bib is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for u-diads-bib.

Paper ↗Leaderboard ↓
§ 01 · Leaderboard

Results by metric.

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Class Average Iou

Class Average Iou is the reported evaluation metric for u-diads-bib. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for Class Average Iouverifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01CV-Group
From paper: ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)
verified83.42024Paper ↗Looks wrong?
02CNKI
From paper: ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)
verified77.82024Paper ↗Looks wrong?
03VAI-OCR
From paper: ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)
verified70.72024Paper ↗Looks wrong?
04DeepLabV3+
From paper: U-DIADS-Bib: a full and few-shot pixel-precise dataset for document layout analysis of ancient manuscripts
verified66.52024Paper ↗Looks wrong?

Class Average Iou Few Shot Setting

Class Average Iou Few Shot Setting is the reported evaluation metric for u-diads-bib. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for Class Average Iou Few Shot Settingverifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01CV-Group
From paper: ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)
verified78.42024Paper ↗Looks wrong?
02VAI-OCR
From paper: ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)
verified702024Paper ↗Looks wrong?
03CNKI
From paper: ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)
verified65.92024Paper ↗Looks wrong?
04L3i++
From paper: ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)
verified61.12024Paper ↗Looks wrong?
§ 04 · Submit a result

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