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SOTA
Text Spotting
Text Spotting On Total Text
Text Spotting On Total Text
Métriques
F-measure (%) - Full Lexicon
F-measure (%) - No Lexicon
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
F-measure (%) - Full Lexicon
F-measure (%) - No Lexicon
Paper Title
Repository
GLASS
83.0
76.6
GLASS: Global to Local Attention for Scene-Text Spotting
DeepSolo (ViTAEv2-S, TextOCR)
89.6
83.6
DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting
DeepSolo (ResNet-50)
87.0
79.7
DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting
SwinTextSpotter
84.1
74.3
SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition
MANGO
83.6
72.9
MANGO: A Mask Attention Guided One-Stage Scene Text Spotter
ABCNet v2
78.1
70.4
ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting
A3S
85.1
79.4
A3S: Adversarial learning of semantic representations for Scene-Text Spotting
-
UNITS
86.0
78.7
Towards Unified Scene Text Spotting based on Sequence Generation
DEER
83.3
74.8
DEER: Detection-agnostic End-to-End Recognizer for Scene Text Spotting
-
MaskTextSpotter v3
78.4
71.2
Mask TextSpotter v3: Segmentation Proposal Network for Robust Scene Text Spotting
DeepSolo (ResNet-50, TextOCR)
88.7
82.5
DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting
TESTR
83.9
73.3
Text Spotting Transformers
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