Graph Matching On Pascal Voc

matching accuracy

Results

Performance results of various models on this benchmark

Comparison Table

Model Name	matching accuracy
neural-graph-matching-network-learning	0.6413
deep-graph-matching-under-quadratic	0.703
glmnet-graph-learning-matching-networks-for	0.675
hypergraph-neural-networks-for-hypergraph	0.680
gamnet-robust-feature-matching-via-graph	0.807
deep-graph-matching-under-quadratic	0.693
deep-learning-of-partial-graph-matching-via	-
learning-latent-partial-matchings-with-gumbel	-
deep-learning-of-partial-graph-matching-via	-
learning-deep-graph-matching-with-channel	0.6756
deep-graph-matching-via-blackbox	-
joint-deep-multi-graph-matching-and-3d	0.589
neural-graph-matching-network-learning	0.6458
universe-points-representation-learning-for	0.818
deep-learning-of-partial-graph-matching-via	-
gmtr-graph-matching-transformers	0.8411
gmtr-graph-matching-transformers	0.836
learning-constrained-structured-spaces-with	-
ia-gm-a-deep-bidirectional-learning-method	0.6658
adaptive-edge-attention-for-graph-matching	0.705
cross-modal-retrieval-with-noisy	0.814
neural-graph-matching-network-learning	0.8040
deep-learning-of-partial-graph-matching-via	-
learning-constrained-structured-spaces-with	-
appearance-and-structure-aware-robust-deep	0.8115
combinatorial-learning-of-robust-deep-graph	0.6770
learning-constrained-structured-spaces-with	-
deep-graph-matching-via-blackbox	0.801
graph-context-attention-networks-for-size	0.8223
deep-learning-of-graph-matching	0.6240
graph-matching-with-bi-level-noisy	0.8267