FOTS MS

Reported on 5 benchmarks across 1 task · 1 paper · 5 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision5 results

Scene Text DetectiononICDAR 2017 MLT
Precision· 2018-01-05
81.86
best: 84.42 (PMTD*)
SOTA
FOTS: Fast Oriented Text Spotting with a Unified Network arXiv:1801.01671
Scene Text DetectiononICDAR 2017 MLT
Recall· 2018-01-05
62.3
best: 76.44 (SBD)
SOTA
FOTS: Fast Oriented Text Spotting with a Unified Network arXiv:1801.01671
Scene Text DetectiononICDAR 2015
F-Measure· 2018-01-05
89.84
best: 92.23 (TextFuseNet (ResNeXt-101))
SOTA
FOTS: Fast Oriented Text Spotting with a Unified Network arXiv:1801.01671
Scene Text DetectiononICDAR 2015
Precision· 2018-01-05
91.85
best: 93.96 (TextFuseNet (ResNeXt-101))
SOTA
FOTS: Fast Oriented Text Spotting with a Unified Network arXiv:1801.01671
Scene Text DetectiononICDAR 2015
Recall· 2018-01-05
87.92
best: 91.98 (CharNet H-88 (single-scale))
SOTA
FOTS: Fast Oriented Text Spotting with a Unified Network arXiv:1801.01671