Action Segmentation On Breakfast 1

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Results

Performance results of various models on this benchmark

							Paper Title	Repository
AdaFocus (newly extracted I3D-features, LT-Context model)	78.0	76.2	78.3	82.1	79.0	67.5	Towards Weakly Supervised End-to-end Learning for Long-video Action Recognition	-
ASQuery	77.9	74.6	78.4	80.7	76.5	66.5	ASQuery: A Query-based Model for Action Segmentation	-
SF-TMN(ASFormer)	77.0	71.6	77.0	78.7	74.0	62.2	SF-TMN: SlowFast Temporal Modeling Network for Surgical Phase Recognition	-
BaFormer	76.6	72.4	77.3	79.2	74.9	63.2	Efficient Temporal Action Segmentation via Boundary-aware Query Voting
DiffAct	76.4	73.6	78.4	80.3	75.9	64.6	Diffusion Action Segmentation
FACT (efficient hybrid of convolution and transformer model)	76.2	74.7	79.7	81.4	76.5	66.2	FACT: Frame-Action Cross-Attention Temporal Modeling for Efficient Action Segmentation	-
C2F-TCN	76.0	66.2	69.6	72.2	68.7	57.6	Coarse to Fine Multi-Resolution Temporal Convolutional Network
ASPnet	75.9	70.6	76.3	78.1	72.9	60.8	ASPnet: Action Segmentation With Shared-Private Representation of Multiple Data Sources	-
BIT	75.5	73.7	79.0	80.6	75.8	64.7	BIT: Bi-Level Temporal Modeling for Efficient Supervised Action Segmentation	-
EUT	75	69.3	74.6	76.2	71.8	59.8	Do we really need temporal convolutions in action segmentation?
CETNet	74.9	71.8	77.8	79.3	74.3	61.9	Cross-Enhancement Transformer for Action Segmentation
LTContext	74.2	70.1	77.0	77.6	72.6	60.1	How Much Temporal Long-Term Context is Needed for Action Segmentation?
ASFormer	73.5	68.0	75.0	76.0	70.6	57.4	ASFormer: Transformer for Action Segmentation
DPRN	71.7	67.9	75.1	75.6	70.5	57.6	Maximization and restoration: Action segmentation through dilation passing and temporal reconstruction	-
DA	71.0	66.4	73.6	74.2	68.6	56.5	Action Segmentation with Mixed Temporal Domain Adaptation	-
G2L(SSTDA)	70.8	66.9	74.5	76.3	69.9	54.6	Global2Local: Efficient Structure Search for Video Action Segmentation
RF++-SSTDA	70.8	-	-	-	-	-	RF-Next: Efficient Receptive Field Search for Convolutional Neural Networks
DS-TCN	70.75	59.6	69.02	67.70	62.05	49.18	Depthwise Separable Temporal Convolutional Network for Action Segmentation	-
BCN	70.4	63.1	66.2	68.7	65.5	55.0	Boundary-Aware Cascade Networks for Temporal Action Segmentation	-
SSTDA	70.2	66.4	73.7	75.0	69.1	55.2	Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation

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Action Segmentation On Breakfast 1

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Results