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Alphazzle: Jigsaw Puzzle Solver with Deep Monte-Carlo Tree Search
Solving jigsaw puzzles requires to grasp the visual features of a sequence of patches and to explore efficiently a solution space that grows exponentially with the sequence length.
Deepzzle: Solving Visual Jigsaw Puzzles with Deep Learning andShortest Path Optimization
We use a two-step method to obtain the reassemblies: 1) a neural network predicts the positions of the fragments despite the gaps between them; 2) a graph that leads to the best reassemblies is made from these predictions.
Image Reassembly Combining Deep Learning and Shortest Path Problem
This paper addresses the problem of reassembling images from disjointed fragments.
Jigsaw Puzzle Solving Using Local Feature Co-Occurrences in Deep Neural Networks
Archaeologists are in dire need of automated object reconstruction methods.
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