The Missing GAP: From Solving Square Jigsaw Puzzles to Handling Real World Archaeological Fragments

2026-05-12

AI Summary

This study addresses the limitations of existing jigsaw puzzle algorithms, which are predominantly designed for regular square pieces and struggle with the irregular shapes and severe erosion characteristic of real-world archaeological fragments. To bridge this gap, the authors introduce GAP, the first irregular jigsaw puzzle dataset closely mirroring authentic archaeological conditions, and propose PuzzleFlow—a novel, general-purpose solving framework that uniquely integrates Vision Transformers (ViT) with Flow Matching. PuzzleFlow is further enhanced by a learning-based model for generating realistic fragment shapes. Experimental results demonstrate that the proposed method significantly outperforms both classical and state-of-the-art algorithms on the GAP benchmark, exhibiting high reconstruction accuracy and strong robustness in handling complex, irregular fragments.

Abstract

Jigsaw puzzle solving has been an increasingly popular task in the computer vision research community. Recent works have utilized cutting-edge architectures and computational approaches to reassemble groups of pieces into a coherent image, while achieving increasingly good results on well established datasets. However, most of these approaches share a common, restricting setting: operating solely on strictly square puzzle pieces. In this work, we introduce GAP, a set of novel jigsaw puzzles datasets containing synthetic, heavily eroded pieces of unrestricted shapes, generated by a learned distribution of real-world archaeological fragments. We also introduce PuzzleFlow, a novel ViT and Flow-Matching based framework for jigsaw puzzle solving, capable of handling complex puzzle pieces and demonstrating superior performance on GAP when compared to both classic and recent prominent works in this domain.

Problem

• jigsaw puzzle solving
• archaeological fragments
• irregular shapes
• fragment reassembly
• non-square pieces

Innovation

• jigsaw puzzle solving
• irregular fragments
• archaeological reconstruction
• Vision Transformer
• Flow-Matching