paper-with-me

Papers

DiffusionSTR: Diffusion Model for Scene Text Recognition

2023-06-29 · Masato Fujitake

This paper presents Diffusion Model for Scene Text Recognition (DiffusionSTR), an end-to-end text recognition framework using diffusion models for recognizing text in the wild. While existing studies have viewed the scene text recognition task as an image-to-text transformation, we rethought it as a text-text one under images in a diffusion model. We show for the first time that the diffusion model can be applied to text recognition. Furthermore, experimental results on publicly available datasets show that the proposed method achieves competitive accuracy compared to state-of-the-art methods.

📄 PDF Abstract BibTeX arXiv:2306.16707

Code (0)

등록된 구현이 없습니다.

Tasks

Image to textmodelScene Text Recognition

Methods 이 논문이 사용한 방법론

Diffusion Diffusion models generate samples by gradually removing noise from a signal, and their training objective can be expressed as a reweighted variational lower-bound…

Similar Papers 제목 키워드 기반

Recognition-Guided Diffusion Model for Scene Text Image Super-Resolution

2023-11-22 · Yuxuan Zhou, Liangcai Gao, Zhi Tang, Baole Wei

Scene Text Image Super-Resolution (STISR) aims to enhance the resolution and legibility of text within low-resolution (LR) images, consequently elevating recognition accuracy in Scene Text Recognition (STR). Previous met…

DenoisingDiversityImage Super-ResolutionScene Text Recognition+1

On Manipulating Scene Text in the Wild with Diffusion Models

2023-11-01 · Joshua Santoso, Christian Simon, Williem Pao

Diffusion models have gained attention for image editing yielding impressive results in text-to-image tasks. On the downside, one might notice that generated images of stable diffusion models suffer from deteriorated det…

Optical Character RecognitionOptical Character Recognition (OCR)Scene Text Editing

TextSSR: Diffusion-based Data Synthesis for Scene Text Recognition

2024-12-02 · Xingsong Ye, Yongkun Du, Yunbo Tao, Zhineng Chen

Scene text recognition (STR) suffers from the challenges of either less realistic synthetic training data or the difficulty of collecting sufficient high-quality real-world data, limiting the effectiveness of trained STR…

Image GenerationOptical Character Recognition (OCR)Scene Text EditingScene Text Recognition

Diffusion in the Dark: A Diffusion Model for Low-Light Text Recognition

2023-03-07 · Cindy M. Nguyen, Eric R. Chan, Alexander W. Bergman, Gordon Wetzstein

Capturing images is a key part of automation for high-level tasks such as scene text recognition. Low-light conditions pose a challenge for high-level perception stacks, which are often optimized on well-lit, artifact-fr…

Image ReconstructionScene Text Recognition

Layout Agnostic Scene Text Image Synthesis with Diffusion Models

2024-06-03 · CVPR 2024 1 · Qilong Zhangli, Jindong Jiang, Di Liu, Licheng Yu 외

While diffusion models have significantly advanced the quality of image generation their capability to accurately and coherently render text within these images remains a substantial challenge. Conventional diffusion-bas…

DiversityImage GenerationInstance SegmentationLayout Generation+2