Action Segmentation On Gtea 1

Métriques

Acc

Edit

F1@10%

F1@25%

F1@50%

Résultats

Résultats de performance de divers modèles sur ce benchmark

Tableau comparatif

Nom du modèle	Acc	Edit	F1@10%	F1@25%	F1@50%
sf-tmn-slowfast-temporal-modeling-network-for	83.0	88.9	91.9	90.7	83.1
is-weakly-supervised-action-segmentation	69.2	84.0	88.2	85.5	67.3
ms-tcn-multi-stage-temporal-convolutional	79.2	81.4	87.5	85.4	74.6
alleviating-over-segmentation-errors-by	77.3	83.7	89.4	87.8	79.8
refining-action-segmentation-with	76.9	84.5	89.2	87.2	74.8
temporal-deformable-residual-networks-for	70.1	74.1	79.2	74.4	62.7
maximization-and-restoration-action	82.0	90.9	92.9	92.0	82.9
bridge-prompt-towards-ordinal-action	81.2	91.6	94.1	92.0	83.0
efficient-temporal-action-segmentation-via	83.0	88.7	92.0	91.3	83.5
diffusion-action-segmentation	82.2	89.6	92.5	91.5	84.7
asformer-transformer-for-action-segmentation	79.7	84.6	90.1	88.8	79.2
boundary-aware-cascade-networks-for-temporal	79.8	84.4	88.5	87.1	77.3
depthwise-separable-temporal-convolutional	78.10	84.05	88.30	85.44	72.84
fact-frame-action-cross-attention-temporal	84.5	93.5	96.1	95.6	87.5
ms-tcn-multi-stage-temporal-convolutional-2	80.1	83.5	88.8	85.7	76.0
unified-fully-and-timestamp-supervised	80.2	92.1	92.7	91.3	81
temporal-convolutional-networks-for-action	64.0	-	72.2	69.3	56.0
cross-enhancement-transformer-for-action	80.3	87.9	91.8	91.2	81.3
bit-bi-level-temporal-modeling-for-efficient	82.0	92.6	94.8	92.8	82.6
refining-action-segmentation-with	78.7	87.5	90.9	88.6	76.4
coarse-to-fine-multi-resolution-temporal	80.8	86.4	90.3	88.8	77.7
action-segmentation-with-joint-self	79.8	86.2	90.0	89.1	78.0
efficient-u-transformer-with-boundary-aware	77	83.9	88.2	87.2	74
ms-tcn-multi-stage-temporal-convolutional-2	79.7	83.0	88.2	86.2	75.9
efficient-two-step-networks-for-temporal	78.2	86.2	91.1	90.0	77.9
action-segmentation-with-mixed-temporal	80.0	85.8	90.5	88.4	76.2
semantic2graph-graph-based-multi-modal	89.8	92.0	95.7	94.2	91.3
segmental-spatiotemporal-cnns-for-fine	60.6	-	58.7	54.4	41.9