Solving jigsaw puzzles is a classic problem in computer vision with various applications. Over the past decades, many useful
approaches have been introduced. Most existing works use edge-wise similarity measures for assembling puzzles with square
pieces of the same size, and recent work innovates to use the loop constraint to improve efficiency and accuracy. We observe that
most existing techniques cannot be easily extended to puzzles with rectangular pieces of arbitrary sizes, and no existing loop
constraints can be used to model such challenging scenarios. In this paper, we propose a new corner-wise matching approach,
modelled using the MatchLift framework to solve square puzzles with cycle consistency. We further show one exciting example
illustrating how puzzles with rectangular pieces of arbitrary sizes would be solved by our techniqu
