Point Clouds On Tanks And Temples
Metrics
Mean F1 (Intermediate)
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Mean F1 (Intermediate) |
|---|---|
| mvsnet-depth-inference-for-unstructured-multi | 43.48 |
| mvsformer-learning-robust-image | 66.37 |
| multi-view-stereo-representation-revist | 65.72 |
| cost-volume-pyramid-based-depth-inference-for | 54.03 |
| visibility-aware-multi-view-stereo-network | 60.03 |
| aa-rmvsnet-adaptive-aggregation-recurrent | 61.51 |
| generalized-binary-search-network-for-highly | 61.42 |
| geomvsnet-learning-multi-view-stereo-with | 65.89 |
| patchmatchnet-learned-multi-view-patchmatch | 53.15 |
| 190408103 | 57.27 |
| epp-mvsnet-epipolar-assembling-based-depth | 61.68 |
| adaptive-patch-deformation-for-textureless | 63.64 |
| dual-level-precision-edges-guided-multi-view | 63.98 |
| ib-mvs-an-iterative-algorithm-for-deep-multi | 56.02 |
| when-epipolar-constraint-meets-non-local-1 | 65.49 |
| mvsformer-revealing-the-devil-in-transformer | 67.03 |
| cascade-cost-volume-for-high-resolution-multi | 56.84 |
| gc-mvsnet-multi-view-multi-scale | 62.74 |
| curvature-guided-dynamic-scale-networks-for-1 | 61.58 |
| deep-stereo-using-adaptive-thin-volume | 54.83 |
| structure-from-motion-revisited | 42.14 |