This paper presents a comprehensive evaluation of the Optical Character Recognition
(OCR) capabilities of the recently released GPT-4V (ision), a Large Multimodal Model …

Scene text images contain not only style information (font background) but also content
information (character texture). Different scene text tasks need different information but …

Despite significant strides in multimodal tasks, Multimodal Large Language Models (MLLMs)
are plagued by the critical issue of hallucination. The reliable detection of such …

Pre-trained vision-language models~(VLMs) are the de-facto foundation models for various
downstream tasks. However, scene text recognition methods still prefer backbones pre …

Modularity plays a crucial role in the development and maintenance of complex systems.
While end-to-end text spotting efficiently mitigates the issues of error accumulation and sub …

In this paper we propose a novel framework to fully exploit the potential of a single vector for
scene text recognition (STR). Different from previous sequence-to-sequence methods that …

Scene text recognition (STR) in the wild frequently encounters challenges when coping with
domain variations font diversity shape deformations etc. A straightforward solution is …

In text recognition, self-supervised pre-training emerges as a good solution to reduce
dependence on expansive annotated real data. Previous studies primarily focus on local …

Scene Text Recognition (STR) is challenging because of various text styles, shapes, and
backgrounds. Although the integration of linguistic information enhances models' …

Existing scene text spotters are designed to locate and transcribe texts from images.
However, it is challenging for a spotter to achieve precise detection and recognition of scene …