Action Segmentation On 50 Salads 1

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F1@10%

F1@25%

F1@50%

Results

Performance results of various models on this benchmark

						Paper Title
Br-Prompt+ASPnet (RGB, flow, accelerometer)	91.4	87.5	92.7	91.6	88.5	ASPnet: Action Segmentation With Shared-Private Representation of Multiple Data Sources
SF-TMN(ASFormer)	89.8	84.4	89.1	88.0	82.9	SF-TMN: SlowFast Temporal Modeling Network for Surgical Phase Recognition
BaFormer	89.5	84.2	89.3	88.4	83.9	Efficient Temporal Action Segmentation via Boundary-aware Query Voting
DiffAct	88.9	85.0	90.1	89.2	83.7	Diffusion Action Segmentation
Semantic2Graph	88.6	89.1	91.5	90.2	87.3	Semantic2Graph: Graph-based Multi-modal Feature Fusion for Action Segmentation in Videos
Br-Prompt+ASFormer	88.1	83.8	89.2	87.8	81.3	Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos
LTContext	87.7	83.2	89.4	87.7	82.0	How Much Temporal Long-Term Context is Needed for Action Segmentation?
EUT	87.4	82.9	89.2	87.5	81	Do we really need temporal convolutions in action segmentation?
UVAST	87.4	83.9	89.1	87.6	81.7	Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation
DPRN	87.2	82.0	87.8	86.3	79.4	Maximization and restoration: Action segmentation through dilation passing and temporal reconstruction
CETNet	86.9	81.7	87.6	86.5	80.1	Cross-Enhancement Transformer for Action Segmentation
ASFormer+ASRF	85.9	81.9	85.1	85.4	79.3	ASFormer: Transformer for Action Segmentation
ASFormer	85.6	79.6	85.1	83.4	76.0	ASFormer: Transformer for Action Segmentation
C2F-TCN	84.9	76.4	84.3	81.8	72.6	Coarse to Fine Multi-Resolution Temporal Convolutional Network
ASRF	84.5	79.3	84.9	83.5	77.3	Alleviating Over-segmentation Errors by Detecting Action Boundaries
BCN	84.4	74.3	82.3	81.3	74	Boundary-Aware Cascade Networks for Temporal Action Segmentation
ASRF + HASR	83.9	81.0	86.6	85.7	78.5	Refining Action Segmentation With Hierarchical Video Representations
MS-TCN++	83.7	74.3	80.7	78.5	70.1	MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation
SSTDA	83.2	75.8	83.0	81.5	73.8	Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
DA	83.2	75.2	82.0	80.1	72.5	Action Segmentation with Mixed Temporal Domain Adaptation

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Action Segmentation On 50 Salads 1

Metrics

Results