Learning from One Continuous Video Stream

arXiv:2312.00598v2 Announce Type: replace
Abstract: We introduce a framework for online learning from a single continuous video stream -- the way people and animals learn, without mini-batches, data augmentation or shuffling. This poses great challenges given the high correlation between consecutive video frames and there is very little prior work on it. Our framework allows us to do a first deep dive into the topic and includes a collection of streams and tasks composed from two existing video datasets, plus …

abstract animals arxiv augmentation challenges continuous correlation cs.ai cs.cv data framework learn online learning people prior the way type video work