Papers › Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers
Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers
Michal Rolínek, Paul Swoboda, Dominik Zietlow, Anselm Paulus, Vít Musil, Georg Martius
Building on recent progress at the intersection of combinatorial optimization and deep learning, we propose an end-to-end trainable architecture for deep graph matching that contains unmodified combinatorial solvers. Using the presence of heavily optimized combinatorial solvers together with some improvements in architecture design, we advance state-of-the-art on deep graph matching benchmarks for keypoint correspondence. In addition, we highlight the conceptual advantages of incorporating solvers into deep learning architectures, such as the possibility of post-processing with a strong multi-graph matching solver or the indifference to changes in the training setting. Finally, we propose two new challenging experimental setups. The code is available at https://github.com/martius-lab/blackbox-deep-graph-matching
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Code
Syntology Ran 5 of 11 code samples harvested from 2 repositories linked to this paper; 6 have no recorded run. Of those that ran: 1 ran · violated contract; 3 ran · our draft was wrong; 1 ran · fixture could not drive it.
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Graph Matching | PASCAL VOC | BBGM-Multi | F1 score | 0.628 | #2 of 31 | Archive leaderboard | report |
| Graph Matching | PASCAL VOC | BBGM | F1 score | 0.614 | #5 of 31 | Archive leaderboard | report |
| Graph Matching | PASCAL VOC | BBGM | matching accuracy | 0.801 | #5 of 31 | Archive leaderboard | report |
| Graph Matching | SPair-71k | BBGM | matching accuracy | 0.8215 | #5 of 8 | Archive leaderboard | report |
| Graph Matching | Willow Object Class | BBGM | matching accuracy | 0.9718 | #10 of 23 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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