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Marie-Morgane Paumard

4 papers hereh-index 3115 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedDeepzzle: Solving Visual Jigsaw Puzzles with Deep Learning andShortest Path Optimization

70 citations · 72 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 2 cited

Alphazzle: Jigsaw Puzzle Solver with Deep Monte-Carlo Tree Search

Marie-Morgane Paumard, Hedi Tabia, David Picard

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.…

cs.CV2020★ 70 cited

Deepzzle: Solving Visual Jigsaw Puzzles with Deep Learning andShortest Path Optimization

Marie-Morgane Paumard, David Picard, Hedi Tabia

We tackle the image reassembly problem with wide space between the fragments, in such a way that the patterns and colors continuity is mostly unusable. The spacing emulates the ero…

cs.CV2018

Image Reassembly Combining Deep Learning and Shortest Path Problem

M. -M. Paumard, D. Picard, H. Tabia

This paper addresses the problem of reassembling images from disjointed fragments. More specifically, given an unordered set of fragments, we aim at reassembling one or several pos…

cs.CV2018

Jigsaw Puzzle Solving Using Local Feature Co-Occurrences in Deep Neural Networks

Marie-Morgane Paumard, David Picard, Hedi Tabia

Archaeologists are in dire need of automated object reconstruction methods. Fragments reassembly is close to puzzle problems, which may be solved by computer vision algorithms. As…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.