Improving Continuous Sign Language Recognition with Adapted Image Models

arXiv:2404.08226v1 Announce Type: new
Abstract: The increase of web-scale weakly labelled image-text pairs have greatly facilitated the development of large-scale vision-language models (e.g., CLIP), which have shown impressive generalization performance over a series of downstream tasks. However, the massive model size and scarcity of available data limit their applications to fine-tune the whole model in downstream tasks. Besides, fully fine-tuning the model easily forgets the generic essential knowledge acquired in the pretraining stage and overfits the downstream data. To enable …

abstract applications arxiv clip continuous cs.cv data development however image improving language language models massive performance recognition scale series tasks text type vision vision-language models web