7 research outputs found
Solving Jigsaw Puzzles with Eroded Boundaries
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 methodsComment: 8 page