Exploiting Instance-based Mixed Sampling via Auxiliary Source Domain Supervision for Domain-adaptive Action Detection. (arXiv:2209.15439v2 [cs.CV] UPDATED)

We propose a novel domain adaptive action detection approach and a new
adaptation protocol that leverages the recent advancements in image-level
unsupervised domain adaptation (UDA) techniques and handle vagaries of
instance-level video data. Self-training combined with cross-domain mixed
sampling has shown remarkable performance gain in semantic segmentation in UDA
(unsupervised domain adaptation) context. Motivated by this fact, we propose an
approach for human action detection in videos that transfers knowledge from the
source domain (annotated dataset) to the target domain …

arxiv detection mixed sampling