15 citations · 26 across the 3 of their papers we have counts for
3 papers
Making the Most of What You Have: Adapting Pre-trained Visual Language Models in the Low-data Regime
Chuhan Zhang, Antoine Miech, Jiajun Shen +2
Large-scale visual language models are widely used as pre-trained models and then adapted for various downstream tasks. While humans are known to efficiently learn new tasks from a…
Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning
Antoine Yang, Arsha Nagrani, Paul Hongsuck Seo +5
In this work, we introduce Vid2Seq, a multi-modal single-stage dense event captioning model pretrained on narrated videos which are readily-available at scale. The Vid2Seq architec…
Zorro: the masked multimodal transformer
Adrià Recasens, Jason Lin, Joāo Carreira +8
Attention-based models are appealing for multimodal processing because inputs from multiple modalities can be concatenated and fed to a single backbone network - thus requiring ver…