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Scene Text Recognition On Iiit5K

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Paper Title
DTrOCR 105M99.6DTrOCR: Decoder-only Transformer for Optical Character Recognition
CLIP4STR-L (DataComp-1B)99.6CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
CLIP4STR-B (DataComp-1B)99.5CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
CLIP4STR-L99.5CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
CPPD99.3Context Perception Parallel Decoder for Scene Text Recognition
CLIP4STR-B99.2CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
PARSeq99.1±0.1Scene Text Recognition with Permuted Autoregressive Sequence Models
MGP-STR98.8Multi-Granularity Prediction for Scene Text Recognition
CCD-ViT-Small(ARD_2.8M)98.0Self-supervised Character-to-Character Distillation for Text Recognition
CCD-ViT-Base(ARD_2.8M)98.0Self-supervised Character-to-Character Distillation for Text Recognition
S-GTR97.5Visual Semantics Allow for Textual Reasoning Better in Scene Text Recognition
DiffusionSTR97.3DiffusionSTR: Diffusion Model for Scene Text Recognition
CCD-ViT-Tiny(ARD_2.8M)97.1Self-supervised Character-to-Character Distillation for Text Recognition
SIGA_S96.9Self-supervised Implicit Glyph Attention for Text Recognition
MATRN96.6Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features
CDistNet (Ours)96.57CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition
DPAN96.2Look Back Again: Dual Parallel Attention Network for Accurate and Robust Scene Text Recognition
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Scene Text Recognition On Iiit5K | SOTA | HyperAI