Model card
GLASS.
UnknownunknownUnknown paramsUnknown
Imported from Papers With Code
§ 01 · Benchmarks
Every benchmark GLASS has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | ICDAR 2015 | Computer Vision · Scene Text Detection | f-measure-generic-lexicon | 76.3% | #6 | 2022-08-05 | source ↗ |
| 02 | Total-Text | Computer Vision · Scene Text Detection | f-measure-no-lexicon | 76.6% | #6 | 2022-08-05 | source ↗ |
| 03 | ICDAR 2015 | Computer Vision · Scene Text Detection | f-measure-weak-lexicon | 80.1% | #7 | 2022-08-05 | source ↗ |
| 04 | ICDAR 2015 | Computer Vision · Scene Text Detection | f-measure-strong-lexicon | 84.7% | #8 | 2022-08-05 | source ↗ |
| 05 | Total-Text | Computer Vision · Scene Text Detection | f-measure-full-lexicon | 83.0% | #10 | 2022-08-05 | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Papers
1 paper with results for GLASS.
- 2022-08-05· Computer Vision· 5 results
GLASS: Global to Local Attention for Scene-Text Spotting
§ 04 · Related models
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§ 05 · Sources & freshness
Where these numbers come from.
papers-with-code
5
results
5 of 5 rows marked verified.