Unsupervised Video Object Segmentation On 11
Metrics
J
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | J |
|---|---|
| treating-motion-as-option-to-reduce-motion | 80.0 |
| treating-motion-as-option-with-output | 83.2 |
| motion-attentive-transition-for-zero-shot | 76.1 |
| guided-slot-attention-for-unsupervised-video | 83.1 |
| deep-transport-network-for-unsupervised-video | 78.7 |
| iteratively-selecting-an-easy-reference-frame | 77.5 |
| treating-motion-as-option-with-output | 81.2 |
| pyramid-dilated-deeper-convlstm-for-video | 74.0 |
| learning-motion-appearance-co-attention-for | 76.5 |
| see-more-know-more-unsupervised-video-object-1 | 75.6 |
| domain-alignment-and-temporal-aggregation-for | 83.4 |
| f2net-learning-to-focus-on-the-foreground-for | 77.5 |
| improving-unsupervised-video-object-1 | 84.7 |
| treating-motion-as-option-to-reduce-motion | 79.9 |
| unsupervised-video-object-segmentation-via | 77.7 |