甲骨文（Oracle bone inscriptions, OBI）是中国最早的成熟文字系统，承载着商代早期历史与古文字学极为珍贵的文字实证。然而在当前学术研究背景下，甲骨文破译工作难度极高：已出土的4500个甲骨文字中，仅三分之一被成功识别。因此，利用先进AI技术辅助甲骨文破译是一项极具必要性的研究课题。但要充分发挥AI在该领域的能力，需要依托全面、高质量的标注甲骨文数据集，而现有多数数据集仅具备单一或少数维度的标注，限制了其潜在应用价值。例如Oracle-MNIST数据集仅提供分为10个类别的3万张图像。为此，本文提出甲骨文多模态数据集（Oracle Bone Inscriptions Multi-modal Dataset, OBIMD），包含10077片甲骨的标注信息。每片甲骨具备两种模态：像素级对齐的拓本与摹本。该数据集标注了每个甲骨文字的检测框、文字类别、释文、对应卜辞组以及组内阅读顺序，提供了全面高质量的标注。该数据集可用于甲骨文领域的多种AI相关研究任务，如甲骨文字检测与识别、拓本去噪、文字匹配、文字生成、阅读顺序预测、缺字补全任务等。我们认为，此类数据集的创建与发布将极大推动AI算法在甲骨文研究领域的应用。
英文摘要：
Oracle bone inscriptions(OBI) is the earliest developed writing system in China, bearing invaluable written exemplifications of early Shang history and paleography. However, the task of deciphering OBI, in the current climate of the scholarship, can prove extremely challenging. Out of the 4,500 oracle bone characters excavated, only a third have been successfully identified. Therefore, leveraging the advantages of advanced AI technology to assist in the decipherment of OBI is a highly essential research topic. However, fully utilizing AI's capabilities in these matters is reliant on having a comprehensive and high-quality annotated OBI dataset at hand whereas most existing datasets are only annotated in just a single or a few dimensions, limiting the value of their potential application. For instance, the Oracle-MNIST dataset only offers 30k images classified into 10 categories. Therefore, this paper proposes an Oracle Bone Inscriptions Multi-modal Dataset(OBIMD), which includes annotation information for 10,077 pieces of oracle bones. Each piece has two modalities: pixel-level aligned rubbings and facsimiles. The dataset annotates the detection boxes, character categories, transcriptions, corresponding inscription groups, and reading sequences in the groups of each oracle bone character, providing a comprehensive and high-quality level of annotations. This dataset can be used for a variety of AI-related research tasks relevant to the field of OBI, such as OBI Character Detection and Recognition, Rubbing Denoising, Character Matching, Character Generation, Reading Sequence Prediction, Missing Characters Completion task and so on. We believe that the creation and publication of a dataset like this will help significantly advance the application of AI algorithms in the field of OBI research.
An open dataset for oracle bone script recognition and decipherment
Huazhong University of Science and Technology（华中科技大学）；The University of Adelaide（阿德莱德大学）；Anyang Normal University（安阳师范学院）；South China University of Technology（华南理工大学）
OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions
School of Computer Science and Technology, East China Normal University（东华大学计算机科学与技术学院）；Institute of Image Communication and Information Processing, Shanghai Jiao Tong University（上海交通大学图像通信与信息处理研究所）；School of Humanities, Shanghai Jiao Tong University（上海交通大学人文学院）；Center for the Study and Application of Chinese Characters, East China Normal University（东华大学汉字研究与应用中心）
PictOBI-20k: Unveiling Large Multimodal Models in Visual Decipherment for Pictographic Oracle Bone Characters
Shanghai Jiao Tong University（上海交通大学）；Shanghai AI Lab（上海人工智能实验室）；Wuhan University（武汉大学）；East China Normal Unversity（华东师范大学）；Macao Polytechnic University（澳门 polytechnic university）；Southern University of Science and Technology（南方科技大学）
Puzzle Pieces Picker: Deciphering Ancient Chinese Characters with Radical Reconstruction
Huazhong University of Science and Technology（华中科技大学）；The University of Adelaide（阿德莱德大学）；Anyang Normal University（安阳师范学院）；South China University of Technology（华南理工大学）
A Cross-Font Image Retrieval Network for Recognizing Undeciphered Oracle Bone Inscriptions
Institute of Artificial Intelligence, Xiamen University（厦门大学人工智能学院）；School of Informatics, Xiamen University（厦门大学信息学院）；Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan (Xiamen University), Ministry of Culture and Tourism（文化和旅游部闽南（厦门大学）非物质文化遗产数字化保护与智能处理重点实验室）
OBI-Bench: Can LMMs Aid in Study of Ancient Script on Oracle Bones?
Institute of Image Communication and Information Processing, Shanghai Jiao Tong University（上海交通大学图像通信与信息处理研究所）；School of Humanities, Shanghai Jiao Tong University（上海交通大学人文学院）
Clustering-based Feature Representation Learning for Oracle Bone Inscriptions Detection
School of Artificial Intelligence（人工智能学院）；School of Archaeology（考古学院）；Engineering Research Center of Knowledge-Driven Human-Machine Intelligence（知识驱动的人机智能工程研究中心）；Key Laboratory of Ancient Chinese Script, Cultural Relics and Artificial Intelligence（古代汉字、文物与人工智能重点实验室）
Ritsumeikan University（立命馆大学）；N.M.A.M Institute of Technology（N.M.A.M理工学院）
Oracle bone inscriptions (OBIs) contain some of the oldest characters in the world and were used in China about 3000 years ago. As an ancient form of literature, OBIs store a lot of information that can help us understand the world history, character evaluations, and more. However, as OBIs were found only discovered about 120 years ago, few studies have described them, and the aging process has made the inscriptions less legible. Hence, automatic character detection and recognition has become an important issue. This paper aims to design a online OBI recognition system for helping preservation…
Enhancing Oracle Bone Inscription Recognition via Multi-Scale Layer Attention
Academy of Chinese Traditional Culture, Sichuan Normal University（四川师范大学中华传统文化学院）；College of Computer Science, Sichuan University（四川大学计算机科学学院）；School of Artificial Intelligence, Sichuan University（四川大学人工智能学院）
Beijing University of Posts and Telecommunications（北京邮电大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；University of Chinese Academy of Sciences（中国科学院大学）
Oracle bone script is the earliest-known Chinese writing system of the Shang dynasty and is precious to archeology and philology. However, real-world scanned oracle data are rare and few experts are available for annotation which make the automatic recognition of scanned oracle characters become a challenging task. Therefore, we aim to explore unsupervised domain adaptation to transfer knowledge from handprinted oracle data, which are easy to acquire, to scanned domain. We propose a structure-texture separation network (STSN), which is an end-to-end learning framework for joint disentanglement…
A comprehensive survey of oracle character recognition: challenges, benchmarks, and beyond
College of Science & Technology Ningbo University（宁波大学科技学院）；School of Advanced Technology, Xi’an Jiaotong-Liverpool University（西交利物浦大学先进技术学院）；Duke Kunshan University（昆山杜克大学）；School of Computer and Information Engineering, Xiamen University of Technology（厦门理工学院计算机与信息工程学院）；Anyang Normal University（安阳师范学院）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）
Deciphering Oracle Bone Language with Diffusion Models
Huazhong University of Science and Technology（华中科技大学）；The University of Adelaide（阿德莱德大学）；Anyang Normal University（安阳师范学院）；South China University of Technology（华南理工大学）
Specializing Large Models for Oracle Bone Script Interpretation via Component-Grounded Multimodal Knowledge Augmentation
College of Software, Jilin University（吉林大学软件学院）；School of Artificial Intelligence, Jilin University（吉林大学人工智能学院）；Graduate School of Information Science and Technology, The University of Tokyo（东京大学信息科学与技术研究生院）；School of Archaeology, Jilin University（吉林大学考古学院）；Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, MoE, China（教育部知识驱动人机智能工程研究中心）
AlphaOracle: Oracle bone script decipherment via human-workflow-inspired deep learning
School of Software Engineering, Huazhong University of Science and Technology（华中科技大学软件学院）；School of Electronic Information Engineering, South China University of Technology（华南理工大学电子信息学院）；Key Laboratory of Oracle Bone Inscriptions Information Processing, Anyang Normal University（安阳师范学院甲骨文信息处理重点实验室）
