However, on-body displacement of sensors is inevitable since the device cannot be firmly worn at a fixed position across different sessions.

Then, MP A denoises the learned prompts through an auto-encoding process and aligns them by maximizing the agreement of all the reconstructed prompts.

Di Lin is the corresponding author of this paper.

Under this setting, previous SSL methods tend to predict wrong pseudo-labels with the model fitted on labeled data, resulting in noise accumulation.

In this study, we delve into the task of few-shot Generative Domain Adaptation (GDA), which involves transferring a pre-trained generator from one domain to a new domain using only a few reference images. Inspired by the way human brains acquire knowledge in new domains, we present an innovative generator structure called Domain Re-Modulation (DoRM) .

However, existing video classification models rely on the i.i.d.