Graph Matching On Willow Object Class
평가 지표
matching accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
모델 이름 | matching accuracy |
---|---|
deep-learning-of-graph-matching | 0.7934 |
combinatorial-learning-of-robust-deep-graph | 0.9006 |
graduated-assignment-for-joint-multi-graph | 0.9906 |
graph-context-attention-networks-for-size | 0.9700 |
deep-learning-of-partial-graph-matching-via | - |
glmnet-graph-learning-matching-networks-for | 0.924 |
gmtr-graph-matching-transformers | 0.9813 |
adaptive-edge-attention-for-graph-matching | 0.965 |
deep-graph-matching-under-quadratic | 0.960 |
deep-graph-matching-under-quadratic | 0.977 |
deep-learning-of-partial-graph-matching-via | - |
neural-graph-matching-network-learning | 0.8530 |
graph-matching-with-bi-level-noisy | 0.9910 |
deep-learning-of-partial-graph-matching-via | - |
learning-constrained-structured-spaces-with | 0.987 |
learning-constrained-structured-spaces-with | 0.981 |
gamnet-robust-feature-matching-via-graph | 0.9662 |
neural-graph-matching-network-learning | 0.9754 |
cross-modal-retrieval-with-noisy | 0.988 |
hypergraph-neural-networks-for-hypergraph | 0.968 |
deep-learning-of-partial-graph-matching-via | - |
universe-points-representation-learning-for | 0.989 |
deep-graph-matching-via-blackbox | 0.9718 |