PGNet is a point-gathering network for reading arbitrarily-shaped text in real-time. It is a single-shot text spotter, where the pixel-level character classification map is learned with proposed PG-CTC loss avoiding the usage of character-level annotations. With a PG-CTC decoder, we gather high-level character classification vectors from two-dimensional space and decode them into text symbols without NMS and RoI operations involved, which guarantees high efficiency. Additionally, reasoning the relations between each character and its neighbors, a graph refinement module (GRM) is proposed to optimize the coarse recognition and improve the end-to-end performance.
Source: PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering NetworkPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Time Series Analysis | 1 | 20.00% |
Decoder | 1 | 20.00% |
Optical Character Recognition (OCR) | 1 | 20.00% |
Scene Text Detection | 1 | 20.00% |
Text Spotting | 1 | 20.00% |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |