Where Do We (Not) Need Temporal Context in Low-Resource Video Task Adaptation? 事件

Where Do We (Not) Need Temporal Context in Low-Resource Video Task Adaptation? arXiv:2606.03837v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) and probing enable adaptation of foundation models using only a small number of trainable parameters, making it attractive for video understanding where annotation and computation are expensive. However, video PEFT has focused on adapting image-pretrained models, while standard PEFT methods can also be applied to video representati