EpiAgent: An Agent-Centric System for Ancient Inscription Restoration

Ancient inscriptions, as repositories of cultural memory, have suffered centuries of environmental and human-induced degradation. Restoring their intertwined visual and textual integrity poses one of the most demanding challenges in digital heritage preservation. However, existing AI-based approaches often rely on rigid pipelines, struggling to generalize across such complex and heterogeneous real-world degradations.Inspired by the skill-coordinated workflow of human epigraphers, we propose EpiAgent, an agent-centric system that formalizes inscription restoration as a hierarchical planning problem. Following an Observe–Conceive–Execute–Reevaluate paradigm, an LLM-based central planner orchestrates collaboration among multimodal analysis, historical experience, specialized restoration tools, and iterative self-refinement. This agent-centric coordination enables a flexible and adaptive restoration process beyond conventional single-pass methods.Across real-world degraded inscriptions, EpiAgent delivers superior restoration quality and stronger generalization compared to existing methods. Our work marks a pivotal step toward expert-level agent-driven restoration of cultural heritage. Code will be released.