الرئيسية الأخبار أحدث الأوراق البحثية الدروس مجموعات البيانات الموسوعة SOTA نماذج LLM لوحة الأداء GPU الفعاليات

العربية

النظام

Scene Text Recognition On Iiit5K

المقاييس

Accuracy

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	Accuracy	Paper Title	Repository
DPAN	96.2	Look Back Again: Dual Parallel Attention Network for Accurate and Robust Scene Text Recognition
CLIP4STR-B (DataComp-1B)	99.5	CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model	-
SIGA_S	96.9	Self-supervised Implicit Glyph Attention for Text Recognition
MATRN	96.6	Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features
DTrOCR 105M	99.6	DTrOCR: Decoder-only Transformer for Optical Character Recognition
CLIP4STR-L	99.5	CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model	-
MGP-STR	98.8	Multi-Granularity Prediction for Scene Text Recognition
PARSeq	99.1±0.1	Scene Text Recognition with Permuted Autoregressive Sequence Models
CCD-ViT-Small(ARD_2.8M)	98.0	Self-supervised Character-to-Character Distillation for Text Recognition	-
CDistNet (Ours)	96.57	CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition
CCD-ViT-Tiny(ARD_2.8M)	97.1	Self-supervised Character-to-Character Distillation for Text Recognition	-
CLIP4STR-B	99.2	CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model	-
CLIP4STR-L (DataComp-1B)	99.6	CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model	-
CCD-ViT-Base(ARD_2.8M)	98.0	Self-supervised Character-to-Character Distillation for Text Recognition	-
S-GTR	97.5	Visual Semantics Allow for Textual Reasoning Better in Scene Text Recognition
DiffusionSTR	97.3	DiffusionSTR: Diffusion Model for Scene Text Recognition	-
CPPD	99.3	Context Perception Parallel Decoder for Scene Text Recognition

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