Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
Few-shot action recognition aims at quickly adapting a pre-trained model to the novel data
with a distribution shift using only a limited number of samples. Key challenges include how
to identify and leverage the transferable knowledge learned by the pre-trained model. We
therefore propose CDTD, or Causal Domain-Invariant Temporal Dynamics for knowledge
transfer. To identify the temporally invariant and variant representations, we employ the
causal representation learning methods for unsupervised pertaining, and then tune the …
with a distribution shift using only a limited number of samples. Key challenges include how
to identify and leverage the transferable knowledge learned by the pre-trained model. We
therefore propose CDTD, or Causal Domain-Invariant Temporal Dynamics for knowledge
transfer. To identify the temporally invariant and variant representations, we employ the
causal representation learning methods for unsupervised pertaining, and then tune the …
Learning Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
Few-shot action recognition aims at quickly adapting a pre-trained model to the novel data
with a distribution shift using only a limited number of samples. Key challenges include how
to identify and leverage the transferable knowledge learned by the pre-trained model. Our
central hypothesis is that temporal invariance in the dynamic system between latent
variables lends itself to transferability (domain-invariance). We therefore propose DITeD, or
Domain-Invariant Temporal Dynamics for knowledge transfer. To detect the temporal …
with a distribution shift using only a limited number of samples. Key challenges include how
to identify and leverage the transferable knowledge learned by the pre-trained model. Our
central hypothesis is that temporal invariance in the dynamic system between latent
variables lends itself to transferability (domain-invariance). We therefore propose DITeD, or
Domain-Invariant Temporal Dynamics for knowledge transfer. To detect the temporal …
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