Scene Text Models

Point Gathering Network

Introduced by Wang et al. in PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network

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 Network

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Time Series Analysis 1 25.00%
Optical Character Recognition (OCR) 1 25.00%
Scene Text Detection 1 25.00%
Text Spotting 1 25.00%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories