Graph Matching on PASCAL VOC

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F1 score

Rank	Model	F1 score	matching accuracy	Paper	Code	Year
1	URL	0.717±0.005	0.818	Universe Points Representation Learning for Partial Multi-Graph Matching		2022
2	BBGM-Multi	0.628	–	Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers	Thinklab-SJTU/ThinkMatch · martius-lab/blackbox-backprop · martius-lab/blackbox-deep-graph-matching · +2	2020
3	GCAN-AFAT-U	0.620	–	Deep Learning of Partial Graph Matching via Differentiable Top-K	Thinklab-SJTU/ThinkMatch	2023
4	GCAN-AFAT-I	0.616	–	Deep Learning of Partial Graph Matching via Differentiable Top-K	Thinklab-SJTU/ThinkMatch	2023
5	BBGM	0.614	0.801	Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers	Thinklab-SJTU/ThinkMatch · martius-lab/blackbox-backprop · martius-lab/blackbox-deep-graph-matching · +2	2020
6	NGMv2-AFAT-U	0.602	–	Deep Learning of Partial Graph Matching via Differentiable Top-K	Thinklab-SJTU/ThinkMatch	2023
7	Direct-2HGM	0.601	–	Learning Constrained Structured Spaces with Application to Multi-Graph Matching	HeddaCohenIndelman/Learning-Constrained-Structured-Spaces-with-Application-to-Multi-Graph-Matching	2022
8	NGMv2-AFAT-I	0.599	–	Deep Learning of Partial Graph Matching via Differentiable Top-K	Thinklab-SJTU/ThinkMatch	2023
9	Direct-2GM	0.597	–	Learning Constrained Structured Spaces with Application to Multi-Graph Matching	HeddaCohenIndelman/Learning-Constrained-Structured-Spaces-with-Application-to-Multi-Graph-Matching	2022
10	GUMBEL-IPF	0.588	–	Learning Latent Partial Matchings with Gumbel-IPF Networks	HeddaCohenIndelman/Learning-Latent-Partial-Matchings-with-Gumbel-IPF-Networks	2024
11	Direct-MGM	0.575	–	Learning Constrained Structured Spaces with Application to Multi-Graph Matching	HeddaCohenIndelman/Learning-Constrained-Structured-Spaces-with-Application-to-Multi-Graph-Matching	2022
12	MGM3D	0.429	0.589	Joint Deep Multi-Graph Matching and 3D Geometry Learning from Inhomogeneous 2D Image Collections		2021
13	GMT-BBGM	–	0.8411	GMTR: Graph Matching Transformers	jp-guo/gm-transformer	2023
14	GMTR	–	0.836	GMTR: Graph Matching Transformers	jp-guo/gm-transformer	2023
15	COMMON	–	0.8267	Graph Matching with Bi-level Noisy Correspondence	Thinklab-SJTU/ThinkMatch · Lin-Yijie/Graph-Matching-Networks · xlearning-scu/2023-iccv-common	2022
16	GCAN	–	0.8223	Graph-Context Attention Networks for Size-Varied Deep Graph Matching	zhehengjiang/gcan	2022
17	CREAM	–	0.814	Cross-modal Retrieval with Noisy Correspondence via Consistency Refining and Mining	XLearning-SCU/2024-TIP-CREAM	2024
18	ASAR-GM	–	0.8115	Appearance and Structure Aware Robust Deep Visual Graph Matching: Attack, Defense and Beyond	thinklab-sjtu/robustmatch	2022
19	GAMnet	–	0.807	GAMnet: Robust Feature Matching via Graph Adversarial-Matching Network		2021
20	NHGM-v2	–	0.8040	Neural Graph Matching Network: Learning Lawler's Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching	Thinklab-SJTU/ThinkMatch	2019