Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification
- Introduction.
This package includes the python codes for implementing Temporal Alignment Prediction (TAP) in supervised learning and few-shot action recognition, described in
Bing Su and Ji-Rong Wen. "Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification" ICLR, 2022.
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License & disclaimer.
The codes can be used for research purposes only. This package is strictly for non-commercial academic use only.
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Usage
The “Supervised_Learning” folder contains codes for using TAP in supervised distance learning for sequence data.
The “Few_Shot_Learning” folder contains codes for using TAP in few-shot action recognition.
Please refer to the ReadMe files in the folds.
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Citations
Please cite the following paper if you use the codes:
Bing Su and Ji-Rong Wen, “Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification”, ICLR, 2022.
