Home News Latest Papers Tutorials Datasets Wiki SOTA LLM Models GPU Leaderboard Events

English

Text Spotting On Total Text

Metrics

F-measure (%) - Full Lexicon

F-measure (%) - No Lexicon

Results

Performance results of various models on this benchmark

Model Name	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

0 of 12 row(s) selected.