collaborators

6 papers

cs.CV2026

Beyond Single Character: Evaluating MLLMs for Sentence-Level Oracle Bone Inscription Understanding

Ziqi Li, Zijian Chen, Tingzhu Chen +1

Existing AI-assisted oracle bone inscription (OBI) visual recognition and understanding studies mainly focus on character-level, ignoring the long-form textual coherence and contex…

cs.CV2026

GTPred: Benchmarking MLLMs for Interpretable Geo-localization and Time-of-capture Prediction

Jinnao Li, Zijian Chen, Tingzhu Chen +1

Geo-localization aims to infer the geographic location where an image was captured using observable visual evidence. Traditional methods achieve impressive results through large-sc…

cs.CV2025

PictOBI-20k: Unveiling Large Multimodal Models in Visual Decipherment for Pictographic Oracle Bone Characters

Zijian Chen, Wenjie Hua, Jinhao Li +4

Deciphering oracle bone characters (OBCs), the oldest attested form of written Chinese, has remained the ultimate, unwavering goal of scholars, offering an irreplaceable key to und…

cs.CV2025

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions

Jinhao Li, Zijian Chen, Tingzhu Chen +2

Oracle bone inscriptions (OBIs) are the earliest known form of Chinese characters and serve as a valuable resource for research in anthropology and archaeology. However, most excav…

cs.CV2025

Mitigating Long-tail Distribution in Oracle Bone Inscriptions: Dataset, Model, and Benchmark

Jinhao Li, Zijian Chen, Runze Jiang +3

The oracle bone inscription (OBI) recognition plays a significant role in understanding the history and culture of ancient China. However, the existing OBI datasets suffer from a l…

cs.CV2025

OBI-Bench: Can LMMs Aid in Study of Ancient Script on Oracle Bones?

Zijian Chen, Tingzhu Chen, Wenjun Zhang +1

We introduce OBI-Bench, a holistic benchmark crafted to systematically evaluate large multi-modal models (LMMs) on whole-process oracle bone inscriptions (OBI) processing tasks dem…