Titlebook: Document Analysis and Recognition – ICDAR 2021; 16th International C Josep Lladós,Daniel Lopresti,Seiichi Uchida Conference proceedings 202

AMEND

Scene Text Detection with Scribble Lineng data. However, the annotation costs of scene text detection are huge with traditional labeling methods due to the various shapes of texts. Thus, it is practical and insightful to study simpler labeling methods without harming the detection performance. In this paper, we propose to annotate the te

先鋒派

locus-ceruleus

SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Modelsrld. Specifically, they generate multiple text images with diverse backgrounds, font styles, and text shapes and enable STR models to learn visual patterns that might not be accessible from manually annotated data. In this paper, we introduce a new synthetic text image generator, SynthTIGER, by anal

驕傲

吹牛需要藝術(shù)

A Multi-level Progressive Rectification Mechanism for Irregular Scene Text Recognition perform rectification at the image level once. This may be insufficient for complicated deformations. To this end, we propose a multi-level progressive rectification mechanism, which consists of global and local rectification modules at the image level and a refinement rectification module at the f

有權(quán)威

Encumber

FEDS - Filtered Edit Distance Surrogate from self-paced learning and filters out the training examples that are hard for the surrogate. The filtering is performed by judging the quality of the approximation, using a ramp function, enabling end-to-end training. Following the literature, the experiments are conducted in a post-tuning setup

Fierce

初次登臺