# OpenOCR **Repository Path**: sieding/OpenOCR ## Basic Information - **Project Name**: OpenOCR - **Description**: No description available - **Primary Language**: Python - **License**: Apache-2.0 - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-02-01 - **Last Updated**: 2026-02-01 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

OpenOCR: An Open-Source Toolkit for General-OCR Research and Applications

如果您觉得本项目有帮助，请为我们点亮Star🌟
license PyPI 简体中文 | [English](./README.md)
______________________________________________________________________ OpenOCR 是由复旦大学[FVL实验室](https://fvl.fudan.edu.cn)[姜育刚教授](https://scholar.google.com/citations?user=f3_FP8AAAAAJ)、[陈智能教授](https://zhinchenfd.github.io)指导的OCR团队打造的开源平台，面向「文字检测与识别」、「公式与表格识别」、「文档解析和理解」等通用 OCR 任务。平台集成了统一的训练与评测基准、商用级 OCR 与文档解析系统，以及众多学术论文的核心代码复现。 OpenOCR 致力于构建一个为学术研究与实际应用搭建桥梁的通用 OCR 开源生态，推动 OCR 技术在研究前沿和产业场景中的协同发展与广泛落地。欢迎研究者、开发者和企业使用和提建议。 ## 核心特性 - 🔥**OpenDoc-0.1B: Ultra-Lightweight Document Parsing System with 0.1B Parameters** - ⚡\[[快速开始](./docs/opendoc.md)\] [![HuggingFace](https://img.shields.io/badge/OpenDoc--0.1B-_Demo_on_HuggingFace-yellow?logo=data:image/png;base64,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&labelColor=white)](https://huggingface.co/spaces/topdu/OpenDoc-0.1B-Demo) [![ModelScope](https://img.shields.io/badge/OpenDoc--0.1B-_Demo_on_ModelScope-purple?logo=data:image/svg+xml;base64,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&labelColor=white)](https://modelscope.cn/studios/topdktu/OpenDoc-0.1B-Demo) \[[本地Demo](./docs/opendoc.md#local-demo)\] - 仅有0.1B参数的超轻量文档解析系统 - 两阶段：版面分析[PP-DocLayoutV2](https://www.paddleocr.ai/latest/version3.x/module_usage/layout_analysis.html) + 文本、公式和表格统一识别自研模型[UniRec-0.1B](./docs/unirec.md) - 在UniRec-0.1B的原始版本中，仅支持文本和公式识别。在OpenDoc-0.1B中，我们重建了UniRec-0.1B，使其支持文本、公式和表格识别 - 支持中、英文文档解析 - 在[OmniDocBench (v1.5)](https://github.com/opendatalab/OmniDocBench/tree/main?tab=readme-ov-file#end-to-end-evaluation)上指标为90.57%，超越众多基于多模态大模型的文档解析模型 - 🔥**UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters** - ⚡\[[使用文档](./docs/unirec.md)\] [![arXiv](https://img.shields.io/badge/UniRec--0.1B-论文-b31b1b.svg?logo=arXiv)](https://arxiv.org/pdf/2512.21095) [![HuggingFace](https://img.shields.io/badge/UniRec--0.1B-_Demo_on_HuggingFace-yellow?logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAF8AAABYCAMAAACkl9t/AAAAk1BMVEVHcEz/nQv/nQv/nQr/nQv/nQr/nQv/nQv/nQr/wRf/txT/pg7/yRr/rBD/zRz/ngv/oAz/zhz/nwv/txT/ngv/0B3+zBz/nQv/0h7/wxn/vRb/thXkuiT/rxH/pxD/ogzcqyf/nQvTlSz/czCxky7/SjifdjT/Mj3+Mj3wMj15aTnDNz+DSD9RTUBsP0FRO0Q6O0WyIxEIAAAAGHRSTlMADB8zSWF3krDDw8TJ1NbX5efv8ff9/fxKDJ9uAAAGKklEQVR42u2Z63qjOAyGC4RwCOfB2JAGqrSb2WnTw/1f3UaWcSGYNKTdf/P+mOkTrE+yJBulvfvLT2A5ruenaVHyIks33npl/6C4s/ZLAM45SOi/1FtZPyFur1OYofBX3w7d54Bxm+E8db+nDr12ttmESZ4zludJEG5S7TO72YPlKZFyE+YCYUJTBZsMiNS5Sd7NlDmKM2Eg2JQg8awbglfqgbhArjxkS7dgp2RH6hc9AMLdZYUtZN5DJr4molC8BfKrEkPKEnEVjLbgW1fLy77ZVOJagoIcLIl+IxaQZGjiX597HopF5CkaXVMDO9Pyix3AFV3kw4lQLCbHuMovz8FallbcQIJ5Ta0vks9RnolbCK84BtjKRS5uA43hYoZcOBGIG2Epbv6CvFVQ8m8loh66WNySsnN7htL58LNp+NXT8/PhXiBXPMjLSxtwp8W9f/1AngRierBkA+kk/IpUSOeKByzn8y3kAAAfh//0oXgV4roHm/kz4E2z//zRc3/lgwBzbM2mJxQEa5pqgX7d1L0htrhx7LKxOZlKbwcAWyEOWqYSI8YPtgDQVjpB5nvaHaSnBaQSD6hweDi8PosxD6/PT09YY3xQA7LTCTKfYX+QHpA0GCcqmEHvr/cyfKQTEuwgbs2kPxJEB0iNjfJcCTPyocx+A0griHSmADiC91oNGVwJ69RudYe65vJmoqfpul0lrqXadW0jFKH5BKwAeCq+Den7s+3zfRJzA61/Uj/9H/VzLKTx9jFPPdXeeP+L7WEvDLAKAIoF8bPTKT0+TM7W8ePj3Rz/Yn3kOAp2f1Kf0Weony7pn/cPydvhQYV+eFOfmOu7VB/ViPe34/EN3RFHY/yRuT8ddCtMPH/McBAT5s+vRde/gf2c/sPsjLK+m5IBQF5tO+h2tTlBGnP6693JdsvofjOPnnEHkh2TnV/X1fBl9S5zrwuwF8NFrAVJVwCAPTe8gaJlomqlp0pv4Pjn98tJ/t/fL++6unpR1YGC2n/KCoa0tTLoKiEeUPDl94nj+5/Tv3/eT5vBQ60X1S0oZr+IWRR8Ldhu7AlLjPISlJcO9vrFotky9SpzDequlwEir5beYAc0R7D9KS1DXva0jhYRDXoExPdc6yw5GShkZXe9QdO/uOvHofxjrV/TNS6iMJS+4TcSTgk9n5agJdBQbB//IfF/HpvPt3Tbi7b6I6K0R72p6ajryEJrENW2bbeVUGjfgoals4L443c7BEE4mJO2SpbRngxQrAKRudRzGQ8jVOL2qDVjjI8K1gc3TIJ5KiFZ1q+gdsARPB4NQS4AjwVSt72DSoXNyOWUrU5mQ9nRYyjp89Xo7oRI6Bga9QNT1mQ/ptaJq5T/7WcgAZywR/XlPGAUDdet3LE+qS0TI+g+aJU8MIqjo0Kx8Ly+maxLjJmjQ18rA0YCkxLQbUZP1WqdmyQGJLUm7VnQFqodmXSqmRrdVpqdzk5LvmvgtEcW8PMGdaS23EOWyDVbACZzUJPaqMbjDxpA3Qrgl0AikimGDbqmyT8P8NOYiqrldF8rX+YN7TopX4UoHuSCYY7cgX4gHwclQKl1zhx0THf+tCAUValzjI7Wg9EhptrkIcfIJjA94evOn8B2eHaVzvBrnl2ig0So6hvPaz0IGcOvTHvUIlE2+prqAxLSQxZlU2stql1NqCCLdIiIN/i1DBEHUoElM9dBravbiAnKqgpi4IBkw+utSPIoBijDXJipSVV7MpOEJUAc5Qmm3BnUN+w3hteEieYKfRZSIUcXKMVf0u5wD4EwsUNVvZOtUT7A2GkffHjByWpHqvRBYrTV72a6j8zZ6W0DTE86Hn04bmyWX3Ri9WH7ZU6Q7h+ZHo0nHUAcsQvVhXRDZHChwiyi/hnPuOsSEF6Exk3o6Y9DT1eZ+6cASXk2Y9k+6EOQMDGm6WBK10wOQJCBwren86cPPWUcRAnTVjGcU1LBgs9FURiX/e6479yZcLwCBmTxiawEwrOcleuu12t3tbLv/N4RLYIBhYexm7Fcn4OJcn0+zc+s8/VfPeddZHAGN6TT8eGczHdR/Gts1/MzDkThr23zqrVfAMFT33Nx1RJsx1k5zuWILLnG/vsH+Fv5D4NTVcp1Gzo8AAAAAElFTkSuQmCC&labelColor=white)](https://huggingface.co/spaces/topdu/OpenOCR-UniRec-Demo) [![ModelScope](https://img.shields.io/badge/UniRec--0.1B-_Demo_on_ModelScope-purple?logo=data:image/svg+xml;base64,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&labelColor=white)](https://modelscope.cn/studios/topdktu/OpenOCR-UniRec-Demo) \[[本地Demo](./docs/unirec.md#local-demo)\] \[[HuggingFace模型下载](https://huggingface.co/topdu/unirec-0.1b)\] \[[ModelScope模型下载](https://www.modelscope.cn/models/topdktu/unirec-0.1b)\] \[[UniRec40M Dataset](https://huggingface.co/datasets/topdu/UniRec40M)\] - 识别纯文本（单词、行、段落）、公式（单行、多行）、以及文本与公式混合的内容 - 0.1B 参数量 - 在 4000 万数据（[UniRec40M](https://huggingface.co/datasets/topdu/UniRec40M)）上从零开始训练，不使用任何预训练 - 支持中文和英文文本/公式识别 - 🔥**OpenOCR: A general OCR system with accuracy and efficiency** - ⚡\[[快速开始](./docs/openocr.md#quick-start)\] [![HuggingFace](https://img.shields.io/badge/OpenOCR-_Demo_on_HuggingFace-yellow?logo=data:image/png;base64,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&labelColor=white)](https://huggingface.co/spaces/topdu/OpenOCR-Demo) [![ModelScope](https://img.shields.io/badge/OpenOCR-_Demo_on_ModelScope-purple?logo=data:image/svg+xml;base64,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&labelColor=white)](https://modelscope.cn/studios/topdktu/OpenOCR-Demo) \[[本地Demo](./docs/openocr.md#local-demo)\] \[[模型下载](https://github.com/Topdu/OpenOCR/releases/tag/develop0.0.1)\] \[[PaddleOCR实现](https://paddlepaddle.github.io/PaddleOCR/latest/algorithm/text_recognition/algorithm_rec_svtrv2.html)\] - [技术文档](./docs/openocr.md) - 基于SVTRv2构建的实用OCR系统 - 在[OCR竞赛榜单](https://aistudio.baidu.com/competition/detail/1131/0/leaderboard)上，精度超越[PP-OCRv4](https://paddlepaddle.github.io/PaddleOCR/latest/ppocr/model_list.html)基线4.5%，推理速度保持相近 - [x] 支持中英文文本检测与识别 - [x] 提供服务器端(Server)与移动端(mobile)模型 - [x] 支持自定义数据集微调: [检测模型微调](./docs/finetune_det.md), [识别模型微调](./docs/finetune_rec.md) - [x] [支持导出ONNX模型](#导出onnx模型) - 🔥**SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition (ICCV 2025)** - \[[文档](./configs/rec/svtrv2/)\] [![arXiv](https://img.shields.io/badge/SVTRv2-论文-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2411.15858) \[[模型下载](./configs/rec/svtrv2/readme.md#11-models-and-results)\] \[[数据集下载](./docs/svtrv2.md#downloading-datasets)\] \[[配置/训练/推理](./configs/rec/svtrv2/readme.md#3-model-training--evaluation)\] \[[基准测试](./docs/svtrv2.md#results-benchmark--configs--checkpoints)\] - [技术文档](./docs/svtrv2.md) - 基于[Union14M](https://github.com/Mountchicken/Union14M)构建的场景文本识别统一训练评估基准 - 支持24种场景文本识别方法在大规模真实数据集[Union14M-L-Filter](./docs/svtrv2.md#数据集详情)上的训练，将持续集成前沿方法 - 相比基于合成数据训练的模型，精度提升20-30% - 单一视觉模型实现任意形状文本识别与语言建模 - 在精度与速度上全面超越基于Attention的编解码模型 - [从零训练SOTA模型指南](./docs/svtrv2.md#get-started-with-training-a-sota-scene-text-recognition-model-from-scratch) ## 自研OCR算法 - [**UniRec-0.1B**](./configs/rec/unirec/) (*Yongkun Du, Zhineng Chen, Yazhen Xie, Weikang Bai, Hao Feng, Wei Shi, Yuchen Su, Can Huang, Yu-Gang Jiang. UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters,* Preprint. [Doc](./configs/rec/unirec/), [Paper](https://arxiv.org/pdf/2512.21095)) - [**MDiff4STR**](./configs/rec/mdiff4str/) (*Yongkun Du, Miaomiao Zhao, Songlin Fan, Zhineng Chen\*, Caiyan Jia, Yu-Gang Jiang. MDiff4STR: Mask Diffusion Model for Scene Text Recognition,* AAAI 2026 Oral. [Doc](./configs/rec/mdiff4str/), [Paper](https://arxiv.org/abs/2512.01422)) - [**CMER**](./configs/rec/cmer/) (*Weikang Bai, Yongkun Du, Yuchen Su, Yazhen Xie, Zhineng Chen\*. Complex Mathematical Expression Recognition: Benchmark, Large-Scale Dataset and Strong Baseline,* AAAI 2026. [Doc](./configs/rec/cmer/), [Paper](https://arxiv.org/abs/2512.13731).) - **TextSSR** (*Xingsong Ye, Yongkun Du, Yunbo Tao, Zhineng Chen\*. TextSSR: Diffusion-based Data Synthesis for Scene Text Recognition,* ICCV 2025. [Paper](https://openaccess.thecvf.com/content/ICCV2025/papers/Ye_TextSSR_Diffusion-based_Data_Synthesis_for_Scene_Text_Recognition_ICCV_2025_paper.pdf), [Code](https://github.com/YesianRohn/TextSSR)) - [**SVTRv2**](./configs/rec/svtrv2) (*Yongkun Du, Zhineng Chen\*, Hongtao Xie, Caiyan Jia, Yu-Gang Jiang. SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition,* ICCV 2025. [Doc](./configs/rec/svtrv2/), [Paper](https://openaccess.thecvf.com/content/ICCV2025/html/Du_SVTRv2_CTC_Beats_Encoder-Decoder_Models_in_Scene_Text_Recognition_ICCV_2025_paper.html)) - [**IGTR**](./configs/rec/igtr/) (*Yongkun Du, Zhineng Chen\*, Yuchen Su, Caiyan Jia, Yu-Gang Jiang. Instruction-Guided Scene Text Recognition,* TPAMI 2025. [Doc](./configs/rec/igtr), [Paper](https://ieeexplore.ieee.org/document/10820836)) - [**CPPD**](./configs/rec/cppd/) (*Yongkun Du, Zhineng Chen\*, Caiyan Jia, Xiaoting Yin, Chenxia Li, Yuning Du, Yu-Gang Jiang. Context Perception Parallel Decoder for Scene Text Recognition,* TPAMI 2025. [PaddleOCR Doc](https://github.com/PaddlePaddle/PaddleOCR/blob/main/docs/algorithm/text_recognition/algorithm_rec_cppd.en.md), [Paper](https://ieeexplore.ieee.org/document/10902187)) - [**SMTR&FocalSVTR**](./configs/rec/smtr/) (*Yongkun Du, Zhineng Chen\*, Caiyan Jia, Xieping Gao, Yu-Gang Jiang. Out of Length Text Recognition with Sub-String Matching,* AAAI 2025. [Doc](./configs/rec/smtr/), [Paper](https://ojs.aaai.org/index.php/AAAI/article/view/32285)) - [**DPTR**](./configs/rec/dptr/) (*Shuai Zhao, Yongkun Du, Zhineng Chen\*, Yu-Gang Jiang. Decoder Pre-Training with only Text for Scene Text Recognition,* ACM MM 2024. [Paper](https://dl.acm.org/doi/10.1145/3664647.3681390)) - [**CDistNet**](./configs/rec/cdistnet/) (*Tianlun Zheng, Zhineng Chen\*, Shancheng Fang, Hongtao Xie, Yu-Gang Jiang. CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition,* IJCV 2024. [Paper](https://link.springer.com/article/10.1007/s11263-023-01880-0)) - **MRN** (*Tianlun Zheng, Zhineng Chen\*, Bingchen Huang, Wei Zhang, Yu-Gang Jiang. MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition,* ICCV 2023. [Paper](https://openaccess.thecvf.com/content/ICCV2023/html/Zheng_MRN_Multiplexed_Routing_Network_for_Incremental_Multilingual_Text_Recognition_ICCV_2023_paper.html), [Code](https://github.com/simplify23/MRN)) - **TPS++** (*Tianlun Zheng, Zhineng Chen\*, Jinfeng Bai, Hongtao Xie, Yu-Gang Jiang. TPS++: Attention-Enhanced Thin-Plate Spline for Scene Text Recognition,* IJCAI 2023. [Paper](https://arxiv.org/abs/2305.05322), [Code](https://github.com/simplify23/TPS_PP)) - [**SVTR**](./configs/rec/svtr/) (*Yongkun Du, Zhineng Chen\*, Caiyan Jia, Xiaoting Yin, Tianlun Zheng, Chenxia Li, Yuning Du, Yu-Gang Jiang. SVTR: Scene Text Recognition with a Single Visual Model,* IJCAI 2022 (Long). [PaddleOCR Doc](https://github.com/Topdu/PaddleOCR/blob/main/doc/doc_ch/algorithm_rec_svtr.md), [Paper](https://www.ijcai.org/proceedings/2022/124)) - [**NRTR**](./configs/rec/nrtr/) (*Fenfen Sheng, Zhineng Chen, Bo Xu. NRTR: A No-Recurrence Sequence-to-Sequence Model For Scene Text Recognition,* ICDAR 2019. [Paper](https://arxiv.org/abs/1806.00926)) ## 近期更新 - **2026.01.13**: 🔥 开源 [CMER](./configs/rec/cmer/) 代码和 and [MER-17M](https://huggingface.co/datasets/topdu/MER-17M) 数据集. - **2026.01.07**: 🔥 开源 [UniRec40M](https://huggingface.co/datasets/topdu/UniRec40M) 数据集，包含4000万多层次文本、公式和文本公式混合内容识别数据. - **2025.12.25**: 🔥 新增超轻量级文档解析系统[OpenDoc-0.1B](./docs/opendoc.md) - **2025.11.08**: [MDiff4STR](https://arxiv.org/abs/2512.01422)被AAAI 2026接收为Oral. 详见[Doc](./configs/rec/mdiff4str/) - **2025.11.08**: [CMER](https://arxiv.org/abs/2512.13731)被AAAI 2026接收. 详见[Doc](./configs/rec/cmer/) - **2025.08.20**: 🔥 新增文本和公式识别模型[UniRec-0.1B](https://arxiv.org/pdf/2512.21095) - **2025.07.10**: [SVTRv2](https://openaccess.thecvf.com/content/ICCV2025/html/Du_SVTRv2_CTC_Beats_Encoder-Decoder_Models_in_Scene_Text_Recognition_ICCV_2025_paper.html)被ICCV 2025接收. 详见[文档](./configs/rec/svtrv2/) - **2025.07.10**: [TextSSR](https://openaccess.thecvf.com/content/ICCV2025/papers/Ye_TextSSR_Diffusion-based_Data_Synthesis_for_Scene_Text_Recognition_ICCV_2025_paper.pdf) 被ICCV 2025接收. 详见[Code](https://github.com/YesianRohn/TextSSR). - **2025.03.24**: 🔥 发布自定义数据集微调功能: [检测模型微调](./docs/finetune_det.md), [识别模型微调](./docs/finetune_rec.md) - **2025.03.23**: 🔥 新增[ONNX模型导出功能](#导出onnx模型) - **2025.02.22**: [CPPD](https://ieeexplore.ieee.org/document/10902187)论文被TPAMI录用，详见[文档](./configs/rec/cppd/)与[PaddleOCR文档](https://github.com/PaddlePaddle/PaddleOCR/blob/main/docs/algorithm/text_recognition/algorithm_rec_cppd.en.md) - **2024.12.31**: [IGTR](https://ieeexplore.ieee.org/document/10820836)论文被TPAMI录用，详见[文档](./configs/rec/igtr/) - **2024.12.16**: [SMTR](https://ojs.aaai.org/index.php/AAAI/article/view/32285)论文被AAAI 2025录用，详见[文档](./configs/rec/smtr/) - **2024.12.03**: [DPTR](https://dl.acm.org/doi/10.1145/3664647.3681390)预训练代码合并 - **🔥 2024.11.23 重大更新**: - **OpenOCR通用OCR系统发布** - ⚡\[[快速开始](./docs/openocr.md#quick-start)\] \[[模型下载](https://github.com/Topdu/OpenOCR/releases/tag/develop0.0.1)\] \[[ModelScopeDemo](https://modelscope.cn/studios/topdktu/OpenOCR-Demo)\] \[[Hugging FaceDemo](https://huggingface.co/spaces/topdu/OpenOCR-Demo)\] \[[本地Demo](./docs/openocr.md#local-demo)\] \[[PaddleOCR实现](https://paddlepaddle.github.io/PaddleOCR/latest/algorithm/text_recognition/algorithm_rec_svtrv2.html)\] - [技术文档](./docs/openocr.md) - **SVTRv2论文发布** - \[[论文](https://openaccess.thecvf.com/content/ICCV2025/html/Du_SVTRv2_CTC_Beats_Encoder-Decoder_Models_in_Scene_Text_Recognition_ICCV_2025_paper.html)\] \[[文档](./configs/rec/svtrv2/)\] \[[模型](./configs/rec/svtrv2/readme.md#11-models-and-results)\] \[[数据集](./docs/svtrv2.md#downloading-datasets)\] \[[配置/训练/推理](./configs/rec/svtrv2/readme.md#3-model-training--evaluation)\] \[[基准测试](./docs/svtrv2.md#results-benchmark--configs--checkpoints)\] - [技术文档](./docs/svtrv2.md) - [从零训练SOTA模型指南](./docs/svtrv2.md#get-started-with-training-a-sota-scene-text-recognition-model-from-scratch) ## 算法复现计划 ### 场景文本识别(STR) | 方法 | 会议/期刊 | 训练支持 | 评估支持 | 贡献者 | | --------------------------------------------- | ------------------------------------------------------------------------------------------------ | -------- | -------- | ------------------------------------------- | | [CRNN](./configs/rec/svtrs/) | [TPAMI 2016](https://arxiv.org/abs/1507.05717) | ✅ | ✅ | | | [ASTER](./configs/rec/aster/) | [TPAMI 2019](https://ieeexplore.ieee.org/document/8395027) | ✅ | ✅ | [pretto0](https://github.com/pretto0) | | [NRTR](./configs/rec/nrtr/) | [ICDAR 2019](https://arxiv.org/abs/1806.00926) | ✅ | ✅ | | | [SAR](./configs/rec/sar/) | [AAAI 2019](https://aaai.org/papers/08610-show-attend-and-read-a-simple-and-strong-baseline-for-irregular-text-recognition/) | ✅ | ✅ | [pretto0](https://github.com/pretto0) | | [MORAN](./configs/rec/moran/) | [PR 2019](https://www.sciencedirect.com/science/article/abs/pii/S0031320319300263) | ✅ | ✅ | | | [DAN](./configs/rec/dan/) | [AAAI 2020](https://arxiv.org/pdf/1912.10205) | ✅ | ✅ | | | [RobustScanner](./configs/rec/robustscanner/) | [ECCV 2020](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3160_ECCV_2020_paper.php) | ✅ | ✅ | [pretto0](https://github.com/pretto0) | | [AutoSTR](./configs/rec/autostr/) | [ECCV 2020](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123690732.pdf) | ✅ | ✅ | | | [SRN](./configs/rec/srn/) | [CVPR 2020](https://openaccess.thecvf.com/content_CVPR_2020/html/Yu_Towards_Accurate_Scene_Text_Recognition_With_Semantic_Reasoning_Networks_CVPR_2020_paper.html) | ✅ | ✅ | [pretto0](https://github.com/pretto0) | | [SEED](./configs/rec/seed/) | [CVPR 2020](https://openaccess.thecvf.com/content_CVPR_2020/html/Qiao_SEED_Semantics_Enhanced_Encoder-Decoder_Framework_for_Scene_Text_Recognition_CVPR_2020_paper.html) | ✅ | ✅ | | | [ABINet](./configs/rec/abinet/) | [CVPR 2021](https://openaccess.thecvf.com//content/CVPR2021/html/Fang_Read_Like_Humans_Autonomous_Bidirectional_and_Iterative_Language_Modeling_for_CVPR_2021_paper.html) | ✅ | ✅ | [YesianRohn](https://github.com/YesianRohn) | | [VisionLAN](./configs/rec/visionlan/) | [ICCV 2021](https://openaccess.thecvf.com/content/ICCV2021/html/Wang_From_Two_to_One_A_New_Scene_Text_Recognizer_With_ICCV_2021_paper.html) | ✅ | ✅ | [YesianRohn](https://github.com/YesianRohn) | | PIMNet | [ACM MM 2021](https://dl.acm.org/doi/10.1145/3474085.3475238) | | | TODO | | [SVTR](./configs/rec/svtrs/) | [IJCAI 2022](https://www.ijcai.org/proceedings/2022/124) | ✅ | ✅ | | | [PARSeq](./configs/rec/parseq/) | [ECCV 2022](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136880177.pdf) | ✅ | ✅ | | | [MATRN](./configs/rec/matrn/) | [ECCV 2022](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136880442.pdf) | ✅ | ✅ | | | [MGP-STR](./configs/rec/mgpstr/) | [ECCV 2022](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136880336.pdf) | ✅ | ✅ | | | [LPV](./configs/rec/lpv/) | [IJCAI 2023](https://www.ijcai.org/proceedings/2023/0189.pdf) | ✅ | ✅ | | | [MAERec](./configs/rec/maerec/)(Union14M) | [ICCV 2023](https://openaccess.thecvf.com/content/ICCV2023/papers/Jiang_Revisiting_Scene_Text_Recognition_A_Data_Perspective_ICCV_2023_paper.pdf) | ✅ | ✅ | | | [LISTER](./configs/rec/lister/) | [ICCV 2023](https://openaccess.thecvf.com/content/ICCV2023/papers/Cheng_LISTER_Neighbor_Decoding_for_Length-Insensitive_Scene_Text_Recognition_ICCV_2023_paper.pdf) | ✅ | ✅ | | | [CDistNet](./configs/rec/cdistnet/) | [IJCV 2024](https://link.springer.com/article/10.1007/s11263-023-01880-0) | ✅ | ✅ | [YesianRohn](https://github.com/YesianRohn) | | [BUSNet](./configs/rec/busnet/) | [AAAI 2024](https://ojs.aaai.org/index.php/AAAI/article/view/28402) | ✅ | ✅ | | | DCTC | [AAAI 2024](https://ojs.aaai.org/index.php/AAAI/article/view/28575) | | | TODO | | [CAM](./configs/rec/cam/) | [PR 2024](https://arxiv.org/abs/2402.13643) | ✅ | ✅ | | | [OTE](./configs/rec/ote/) | [CVPR 2024](https://openaccess.thecvf.com/content/CVPR2024/html/Xu_OTE_Exploring_Accurate_Scene_Text_Recognition_Using_One_Token_CVPR_2024_paper.html) | ✅ | ✅ | | | CFF | [IJCAI 2024](https://arxiv.org/abs/2407.05562) | | | TODO | | [DPTR](./configs/rec/dptr/) | [ACM MM 2024](https://dl.acm.org/doi/10.1145/3664647.3681390) | | | [fd-zs](https://github.com/fd-zs) | | VIPTR | [ACM CIKM 2024](https://arxiv.org/abs/2401.10110) | | | TODO | | [IGTR](./configs/rec/igtr/) | [TPAMI 2025](https://ieeexplore.ieee.org/document/10820836) | ✅ | ✅ | | | [SMTR](./configs/rec/smtr/) | [AAAI 2025](https://ojs.aaai.org/index.php/AAAI/article/view/32285) | ✅ | ✅ | | | [CPPD](./configs/rec/cppd/) | [TPAMI 2025](https://ieeexplore.ieee.org/document/10902187) | ✅ | ✅ | | | [FocalSVTR-CTC](./configs/rec/svtrs/) | [AAAI 2025](https://ojs.aaai.org/index.php/AAAI/article/view/32285) | ✅ | ✅ | | | [SVTRv2](./configs/rec/svtrv2/) | [ICCV 2025](https://openaccess.thecvf.com/content/ICCV2025/html/Du_SVTRv2_CTC_Beats_Encoder-Decoder_Models_in_Scene_Text_Recognition_ICCV_2025_paper.html) | ✅ | ✅ | | | [ResNet+Trans-CTC](./configs/rec/svtrs/) | | ✅ | ✅ | | | [ViT-CTC](./configs/rec/svtrs/) | | ✅ | ✅ | | | [MDiff4STR](./configs/rec/mdiff4str/) | [AAAI 2025 Oral](https://arxiv.org/abs/2512.01422) | ✅ | ✅ | | ### 场景文本检测(STD) 开发中 ### 端到端文本识别(Text Spotting) 开发中 ______________________________________________________________________ ## 引用 如果我们的工作对您的研究有所帮助，请引用： ```bibtex @inproceedings{Du2025SVTRv2, title={SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition}, author={Yongkun Du and Zhineng Chen and Hongtao Xie and Caiyan Jia and Yu-Gang Jiang}, booktitle={ICCV}, year={2025}, pages={20147-20156} } @article{du2025unirec, title={UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters}, author={Yongkun Du and Zhineng Chen and Yazhen Xie and Weikang Bai and Hao Feng and Wei Shi and Yuchen Su and Can Huang and Yu-Gang Jiang}, journal={arXiv preprint arXiv:2512.21095}, year={2025} } ``` ## 致谢 本代码库基于[PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)、[PytorchOCR](https://github.com/WenmuZhou/PytorchOCR)和[MMOCR](https://github.com/open-mmlab/mmocr)构建，感谢他们的出色工作！