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|a 10.1109/TPAMI.2023.3284080
|2 doi
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|a pubmed24n1192.xml
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|a eng
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| 100 |
1 |
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|a Singhania, Dipika
|e verfasserin
|4 aut
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| 245 |
1 |
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|a C2F-TCN
|b A Framework for Semi- and Fully-Supervised Temporal Action Segmentation
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|c 2023
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|a Text
|b txt
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Revised 06.09.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Temporal action segmentation tags action labels for every frame in an input untrimmed video containing multiple actions in a sequence. For the task of temporal action segmentation, we propose an encoder-decoder style architecture named C2F-TCN featuring a "coarse-to-fine" ensemble of decoder outputs. The C2F-TCN framework is enhanced with a novel model agnostic temporal feature augmentation strategy formed by the computationally inexpensive strategy of the stochastic max-pooling of segments. It produces more accurate and well-calibrated supervised results on three benchmark action segmentation datasets. We show that the architecture is flexible for both supervised and representation learning. In line with this, we present a novel unsupervised way to learn frame-wise representation from C2F-TCN. Our unsupervised learning approach hinges on the clustering capabilities of the input features and the formation of multi-resolution features from the decoder's implicit structure. Further, we provide first semi-supervised temporal action segmentation results by merging representation learning with conventional supervised learning. Our semi-supervised learning scheme, called "Iterative-Contrastive-Classify (ICC)", progressively improves in performance with more labeled data. The ICC semi-supervised learning in C2F-TCN, with 40% labeled videos, performs similar to fully supervised counterparts
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| 650 |
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|a Journal Article
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| 700 |
1 |
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|a Rahaman, Rahul
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Yao, Angela
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 45(2023), 10 vom: 08. Okt., Seite 11484-11501
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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|g volume:45
|g year:2023
|g number:10
|g day:08
|g month:10
|g pages:11484-11501
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|u http://dx.doi.org/10.1109/TPAMI.2023.3284080
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|d 45
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