Web: http://arxiv.org/abs/2206.07160

June 16, 2022, 1:13 a.m. | Linjie Li, Zhe Gan, Kevin Lin, Chung-Ching Lin, Zicheng Liu, Ce Liu, Lijuan Wang

cs.CV updates on arXiv.org arxiv.org

Unified vision-language frameworks have greatly advanced in recent years,
most of which adopt an encoder-decoder architecture to unify image-text tasks
as sequence-to-sequence generation. However, existing video-language (VidL)
models still require task-specific designs in model architecture and training
objectives for each task. In this work, we explore a unified VidL framework
LAVENDER, where Masked Language Modeling (MLM) is used as the common interface
for all pre-training and downstream tasks. Such unification leads to a
simplified model architecture, where only a lightweight …

arxiv cv language modeling video

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