Semantic Correspondence On Pf Willow
Metriken
PCK
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | PCK | Paper Title | Repository |
|---|---|---|---|
| SCOT | 78.1 | Semantic Correspondence as an Optimal Transport Problem | |
| DHPF | 77.6 | Learning to Compose Hypercolumns for Visual Correspondence | - |
| CHM | 79.4 | Convolutional Hough Matching Networks | - |
| HPF | 76.3 | Hyperpixel Flow: Semantic Correspondence with Multi-layer Neural Features | - |
| VAT | 81.0 | Cost Aggregation Is All You Need for Few-Shot Segmentation | - |
| LDMCorrespondences | 84.3 | Unsupervised Semantic Correspondence Using Stable Diffusion | - |
| CATs | 79.2 | CATs: Cost Aggregation Transformers for Visual Correspondence | - |
| VAT (ECCV) | 81.6 | Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation | - |
0 of 8 row(s) selected.