Datasets › WOST

WOST

Introduced by Yuxin Wang et al. in From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network22 Aug 2021 archive 2025-07-28

The Weakly Occluded Scene Text (WOST) dataset is a public dataset for scene text segmentation. It is used to generate pixel-level annotations in scene text images 1. The dataset is designed to contain weakly annotated images, which means that the images are not fully annotated with pixel-level labels.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Scene Text Recognition WOST CLIP4STR-H (DFN-5B) 1:1 Accuracy 90.9 CLIP4STR: A Simple Baseline for Scene Text Recognition... VamosC/CLIP4STR 5 Compare

Papers archive 2025-07-28

2 shown of 2 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 17. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model 1 4 23 May 2023 ran 3 of 10 samples (7 unverified)
Self-supervised Character-to-Character Distillation for Text Recognition 1 1 1 Nov 2022 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • WOST

1 variant name, as the archive lists them.

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