Model card
SIGA_T.
UnknownunknownUnknown paramsUnknown
Imported from Papers With Code
§ 01 · Benchmarks
Every benchmark SIGA_T has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | icdar-2003 | Computer Vision · Scene Text Recognition | accuracy | 97.0% | #2 | 2022-03-07 | source ↗ |
| 02 | icdar2013 | Computer Vision · Optical Character Recognition | accuracy | 97.8% | #9 | 2022-03-07 | source ↗ |
| 03 | cute80 | Computer Vision · Scene Text Recognition | accuracy | 93.1% | #13 | 2022-03-07 | source ↗ |
| 04 | svtp | Computer Vision · Scene Text Recognition | accuracy | 90.5% | #13 | 2022-03-07 | source ↗ |
| 05 | svt | Computer Vision · Scene Text Recognition | accuracy | 95.1% | #15 | 2022-03-07 | 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 SIGA_T.
- 2022-03-07· Computer Vision· 5 results
Self-supervised Implicit Glyph Attention for Text Recognition
§ 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.