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SOTA
Scene Text Detection
Scene Text Detection On Icdar 2017 Mlt 1
Scene Text Detection On Icdar 2017 Mlt 1
Metrics
F-Measure
Precision
Recall
Results
Performance results of various models on this benchmark
Columns
Model Name
F-Measure
Precision
Recall
Paper Title
PMTD*
80.13%
84.42
76.25
Pyramid Mask Text Detector
Corner Localization (single-scale)
66.8%
83.8
55.6
Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation
SBD
79.47%
82.75
76.44
Exploring the Capacity of an Orderless Box Discretization Network for Multi-orientation Scene Text Detection
FOTS MS
70.75%
81.86
62.3
FOTS: Fast Oriented Text Spotting with a Unified Network
CharNet H-88
75.77%
81.27
70.97
Convolutional Character Networks
FOTS
67.25%
80.95
57.51
FOTS: Fast Oriented Text Spotting with a Unified Network
CRAFT
-
80.6
68.2
Character Region Awareness for Text Detection
SPCNET
74.1%
80.6
68.6
Scene Text Detection with Supervised Pyramid Context Network
PAN
74.3%
80
69.8
Mask R-CNN with Pyramid Attention Network for Scene Text Detection
GNNets
74.54%
79.63
70.06
Geometry Normalization Networks for Accurate Scene Text Detection
CharNet R-50
73.42%
77.07
70.1
Convolutional Character Networks
PSENet-1s
72.45%
77.01
68.4
Shape Robust Text Detection with Progressive Scale Expansion Network
PSENet (ResNet-152)
72.13%
75.35
69.18
Shape Robust Text Detection with Progressive Scale Expansion Network
Corner Localization (multi-scale)
72.4%
74.3
70.6
Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation
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