Weakly Supervised Semantic Segmentation On
評価指標
Mean IoU
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
比較表
| モデル名 | Mean IoU |
|---|---|
| self-supervised-image-specific-prototype | 68.8 |
| pseudo-mask-matters-inweakly-supervised | 68.5 |
| leveraging-instance-image-and-dataset-level | 66.5 |
| uncertainty-estimation-via-response-scaling | 69.4 |
| leveraging-instance-image-and-dataset-level | 69.4 |
| threshold-matters-in-wsss-manipulating-the | 69.5 |
| uncertainty-estimation-via-response-scaling | 70.1 |
| causal-intervention-for-weakly-supervised | 66.1 |
| isim-iterative-self-improved-model-for-weakly | 70.51 |
| leveraging-instance-image-and-dataset-level | 67.8 |
| weaktr-exploring-plain-vision-transformer-for | 74.0 |
| mining-cross-image-semantics-for-weakly | 66.2 |
| saliency-guided-self-attention-network-for | 67.1 |
| all-pairs-consistency-learning-for-weakly | 71.2 |
| inferring-the-class-conditional-response-map | 70.8 |
| pseudo-mask-matters-inweakly-supervised | 68.5 |
| semples-semantic-prompt-learning-for-weakly | 83.4 |
| weakly-supervised-semantic-segmentation-with-1 | 70.6 |
| pseudo-mask-matters-inweakly-supervised | 70.0 |
| unlocking-the-potential-of-ordinary | 68.4 |
| weakly-supervised-semantic-segmentation-via-3 | 71.9 |
| weakly-supervised-semantic-segmentation-using-2 | 70.7 |
| fine-grained-background-representation-for | 74.2 |
| clustering-guided-class-activation-for-weakly | 70.3 |
| learning-self-supervised-low-rank-network-for | 67.2 |
| weakly-supervised-image-semantic-segmentation | 68.7 |
| learning-self-supervised-low-rank-network-for | 69.3 |
| dhr-dual-features-driven-hierarchical | 82.3 |
| from-text-to-mask-localizing-entities-using | 73.3 |
| activation-based-sampling-for-pixel-to-image | 70.1 |
| learning-integral-objects-with-intra-class | 64.1 |
| reducing-information-bottleneck-for-weakly | 68.3 |
| weakly-supervised-semantic-segmentation-with-1 | 70.6 |
| max-pooling-with-vision-transformers | 70.3 |
| weakly-supervised-semantic-segmentation-with-1 | 70.8 |
| railroad-is-not-a-train-saliency-as-pseudo-1 | 70.9 |
| weakly-supervised-semantic-segmentation-by-3 | 72.3 |
| boundary-enhanced-co-training-for-weakly | 72.1 |
| weakly-supervised-learning-of-instance | 63.5 |
| discriminative-region-suppression-for-weakly | 71.0 |
| puzzle-cam-improved-localization-via-matching | 66.9 |
| weakly-supervised-co-training-with-swapping | 76.4 |
| boundary-enhanced-co-training-for-weakly | 73.7 |
| an-alternative-to-wsss-an-empirical-study-of | 77.2 |
| weakly-supervised-co-training-with-swapping | 81.4 |
| railroad-is-not-a-train-saliency-as-pseudo-1 | 71.0 |
| reducing-information-bottleneck-for-weakly | 70.2 |
| integral-object-mining-via-online-attention | 65.2 |
| isim-iterative-self-improved-model-for-weakly | 74.90 |
| l2g-a-simple-local-to-global-knowledge | 72.1 |
| recurseed-and-certainmix-for-weakly | 74.4 |
| weakly-supervised-image-semantic-segmentation | 66.7 |
| discriminative-region-suppression-for-weakly | 70.4 |
| mars-model-agnostic-biased-object-removal | 77.7 |
| uncertainty-estimation-via-response-scaling | 69.5 |
| self-supervised-equivariant-attention | 64.5 |
| recurseed-and-certainmix-for-weakly | 69.5 |
| foundation-model-assisted-weakly-supervised | 82.6 |
| group-wise-semantic-mining-for-weakly | 68.2 |
| regional-semantic-contrast-and-aggregation | 72.2 |
| adaptive-early-learning-correction-for | 71.6 |
| weakly-supervised-semantic-segmentation-via-1 | 66.1 |
| anti-adversarially-manipulated-attributions | 68.1 |
| getam-gradient-weighted-element-wise | 71.7 |
| uncertainty-estimation-via-response-scaling | 71.2 |
| sfc-shared-feature-calibration-in-weakly | 71.2 |
| threshold-matters-in-wsss-manipulating-the | 70.7 |
| weaktr-exploring-plain-vision-transformer-for | 78.4 |
| precision-matters-precision-aware-ensemble | 72.2 |
| puzzle-cam-improved-localization-via-matching | 71.9 |
| complementary-patch-for-weakly-supervised | 67.8 |
| question-answer-cross-language-image-matching | 75.6 |
| clip-is-also-an-efficient-segmenter-a-text | 73.8 |