# Solving Jigsaw Puzzles with Eroded Boundaries

arXiv: https://arxiv.org/abs/1912.00755 · HTML: https://mlsanity.com/paper/1912.00755/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Dec 2019.

## Built on by (most cited first, 14 of 14)

- [JigsawGAN: Auxiliary Learning for Solving Jigsaw Puzzles with Generative Adversarial Networks](https://mlsanity.com/paper/2101.07555/) (2021)
- [Solving Masked Jigsaw Puzzles with Diffusion Vision Transformers](https://mlsanity.com/paper/2404.07292/) (2024)
- [GANzzle: Reframing jigsaw puzzle solving as a retrieval task using a generative mental image](https://mlsanity.com/paper/2207.05634/) (2022)
- [Pairwise Alignment & Compatibility for Arbitrarily Irregular Image Fragments](https://mlsanity.com/paper/2507.09767/) (2025)
- [ERL-MPP: Evolutionary Reinforcement Learning with Multi-head Puzzle Perception for Solving Large-scale Jigsaw Puzzles of Eroded Gaps](https://mlsanity.com/paper/2504.09608/) (2025)
- [Graph Jigsaw Learning for Cartoon Face Recognition](https://mlsanity.com/paper/2107.06532/) (2021)
- [TEN: Twin Embedding Networks for the Jigsaw Puzzle Problem with Eroded Boundaries](https://mlsanity.com/paper/2203.06488/) (2022)
- [VLHSA: Vision-Language Hierarchical Semantic Alignment for Jigsaw Puzzle Solving with Eroded Gaps](https://mlsanity.com/paper/2509.25202/) (2025)
- [The Missing GAP: From Solving Square Jigsaw Puzzles to Handling Real World Archaeological Fragments](https://mlsanity.com/paper/2605.12077/) (2026)
- [Relaxation Labeling Meets GANs: Solving Jigsaw Puzzles with Missing Borders](https://mlsanity.com/paper/2203.14428/) (2022)
- [Edge2Vec: A High Quality Embedding for the Jigsaw Puzzle Problem](https://mlsanity.com/paper/2211.07771/) (2022)
- [Alphazzle: Jigsaw Puzzle Solver with Deep Monte-Carlo Tree Search](https://mlsanity.com/paper/2302.00384/) (2023)
- [JigSync: Gauge-Resolved Synchronization for Jigsaw Reassembly under Unknown Piece Orientation](https://mlsanity.com/paper/2609.18379/) (2026)
- [Fix the Match, Not the Solver: STITCH -- a Self-Supervised Compatibility Measure for Eroded Visual Puzzles](https://mlsanity.com/paper/2610.13176/) (2026)

## Abstract (arXiv)

Jigsaw puzzle solving is an intriguing problem which has been explored in computer vision for decades. This paper focuses on a specific variant of the problem - solving puzzles with eroded boundaries. Such erosion makes the problem extremely difficult, since most existing solvers utilize solely the information at the boundaries. Nevertheless, this variant is important since erosion and missing data often occur at the boundaries. The key idea of our proposed approach is to inpaint the eroded boundaries between puzzle pieces and later leverage the quality of the inpainted area to classify a pair of pieces as 'neighbors or not'. An interesting feature of our architecture is that the same GAN discriminator is used for both inpainting and classification; Training of the second task is simply a continuation of the training of the first, beginning from the point it left off. We show that our approach outperforms other SOTA methods