Unsupervised Video Object Segmentation On 10
المقاييس
F
G
J
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | F | G | J |
|---|---|---|---|
| reciprocal-transformations-for-unsupervised | 84.7 | 85.2 | 85.6 |
| improving-unsupervised-video-object-1 | 89.0 | 88.5 | 88.0 |
| iteratively-selecting-an-easy-reference-frame | 86.7 | 85.6 | 84.5 |
| deep-transport-network-for-unsupervised-video | 85.0 | 84.8 | 84.5 |
| treating-motion-as-option-to-reduce-motion | 87.8 | 87.2 | 86.6 |
| learning-unsupervised-video-object | 77.4 | 78.6 | 79.7 |
| pyramid-dilated-deeper-convlstm-for-video | 74.5 | 75.9 | 77.2 |
| making-a-case-for-3d-convolutions-for-object | 84.7 | 84.5 | 84.3 |
| guided-slot-attention-for-unsupervised-video | 89.6 | 88.9 | 88.3 |
| self-supervised-video-object-segmentation-1 | 86.6 | 85.75 | 84.9 |
| zero-shot-video-object-segmentation-via-1 | 79.1 | 79.9 | 80.7 |
| unsupervised-video-object-segmentation-via | 86.4 | 85.9 | 85.4 |
| treating-motion-as-option-to-reduce-motion | 86.6 | 86.1 | 85.6 |
| adaptive-multi-source-predictor-for-zero-shot | 87.5 | 87.3 | 87.1 |
| tracking-anything-with-decoupled-video | 90.2 | 88.9 | 87.6 |
| motion-attentive-transition-for-zero-shot | 80.7 | 81.6 | 82.4 |
| learning-motion-appearance-co-attention-for | 84.6 | 84.6 | 84.5 |
| d2conv3d-dynamic-dilated-convolutions-for | 86.5 | 86.0 | 85.5 |
| learning-discriminative-feature-with-crf-for | 81.8 | 82.6 | 83.4 |
| full-duplex-strategy-for-video-object | 83.1 | 83.3 | 83.4 |
| domain-alignment-and-temporal-aggregation-for | 88.4 | 87.6 | 86.8 |
| see-more-know-more-unsupervised-video-object-1 | 79.4 | 80.0 | 80.5 |
| f2net-learning-to-focus-on-the-foreground-for | 54.4 | 83.7 | 83.1 |
| anchor-diffusion-for-unsupervised-video-1 | 80.5 | 81.1 | 81.7 |
| unsupervised-video-object-segmentation-with-2 | 80.7 | 81.5 | 82.2 |