Model card
FOTS.
UnknownunknownUnknown paramsUnknown
Imported from Papers With Code
§ 01 · Benchmarks
Every benchmark FOTS has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | icdar-2017-mlt | Computer Vision · Scene Text Detection | precision | 81.0% | #9 | 2018-01-05 | source ↗ |
| 02 | ICDAR 2015 | Computer Vision · Scene Text Detection | f-measure-strong-lexicon | 83.6% | #10 | 2018-01-05 | source ↗ |
| 03 | ICDAR 2015 | Computer Vision · Scene Text Detection | precision | 91.0% | #11 | 2018-01-05 | source ↗ |
| 04 | ICDAR 2015 | Computer Vision · Scene Text Detection | f-measure | 88.0% | #14 | 2018-01-05 | source ↗ |
| 05 | ICDAR 2015 | Computer Vision · Scene Text Detection | recall | 85.2% | #15 | 2018-01-05 | source ↗ |
| 06 | icdar-2017-mlt | Computer Vision · Scene Text Detection | f-measure | 67.3% | #16 | 2018-01-05 | source ↗ |
| 07 | ICDAR 2015 | Computer Vision · Scene Text Detection | f-measure-weak-lexicon | 74.5% | #17 | 2018-01-05 | source ↗ |
| 08 | icdar-2017-mlt | Computer Vision · Scene Text Detection | recall | 57.5% | #17 | 2018-01-05 | source ↗ |
| 09 | ICDAR 2015 | Computer Vision · Scene Text Detection | f-measure-generic-lexicon | 62.2% | #18 | 2018-01-05 | 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 FOTS.
- 2018-01-05· Computer Vision· 9 results
FOTS: Fast Oriented Text Spotting with a Unified Network
§ 04 · Related models
Other Unknown models scored on Codesota.
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§ 05 · Sources & freshness
Where these numbers come from.
papers-with-code
9
results
9 of 9 rows marked verified.