Action Segmentation On Breakfast 1

评估指标

Acc
Average F1
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F1@10%
F1@25%
F1@50%

评测结果

各个模型在此基准测试上的表现结果

Paper TitleRepository
AdaFocus (newly extracted I3D-features, LT-Context model)78.076.278.382.179.067.5Towards Weakly Supervised End-to-end Learning for Long-video Action Recognition-
ASQuery77.974.678.480.776.566.5ASQuery: A Query-based Model for Action Segmentation-
SF-TMN(ASFormer)77.071.677.078.774.062.2SF-TMN: SlowFast Temporal Modeling Network for Surgical Phase Recognition-
BaFormer76.672.477.379.274.963.2Efficient Temporal Action Segmentation via Boundary-aware Query Voting
DiffAct76.473.678.480.375.964.6Diffusion Action Segmentation
FACT (efficient hybrid of convolution and transformer model)76.274.779.781.476.566.2FACT: Frame-Action Cross-Attention Temporal Modeling for Efficient Action Segmentation-
C2F-TCN76.066.269.672.268.757.6Coarse to Fine Multi-Resolution Temporal Convolutional Network
ASPnet75.970.676.378.172.960.8ASPnet: Action Segmentation With Shared-Private Representation of Multiple Data Sources-
BIT75.573.779.080.675.864.7BIT: Bi-Level Temporal Modeling for Efficient Supervised Action Segmentation-
EUT7569.374.676.271.859.8Do we really need temporal convolutions in action segmentation?
CETNet74.971.877.879.374.361.9Cross-Enhancement Transformer for Action Segmentation
LTContext74.270.177.077.672.660.1How Much Temporal Long-Term Context is Needed for Action Segmentation?
ASFormer73.568.075.076.070.657.4ASFormer: Transformer for Action Segmentation
DPRN71.767.975.175.670.557.6Maximization and restoration: Action segmentation through dilation passing and temporal reconstruction-
DA71.066.473.674.268.656.5Action Segmentation with Mixed Temporal Domain Adaptation-
G2L(SSTDA)70.866.974.576.369.954.6Global2Local: Efficient Structure Search for Video Action Segmentation
RF++-SSTDA70.8-----RF-Next: Efficient Receptive Field Search for Convolutional Neural Networks
DS-TCN70.7559.669.0267.7062.0549.18Depthwise Separable Temporal Convolutional Network for Action Segmentation-
BCN70.463.166.268.765.555.0Boundary-Aware Cascade Networks for Temporal Action Segmentation-
SSTDA70.266.473.775.069.155.2Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
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Action Segmentation On Breakfast 1 | SOTA | HyperAI超神经