5.7k citations · 8.2k across the 48 of their papers we have counts for
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cs.CV2023
IG Captioner: Information Gain Captioners are Strong Zero-shot Classifiers
Chenglin Yang, Siyuan Qiao, Yuan Cao +4
Generative training has been demonstrated to be powerful for building visual-language models. However, on zero-shot discriminative benchmarks, there is still a performance gap betw…
cs.CV2022★ 20 cited
VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners
Shen Yan, Tao Zhu, Zirui Wang +5
We explore an efficient approach to establish a foundational video-text model. We present VideoCoCa that maximally reuses a pretrained image-text contrastive captioner (CoCa) model…
cs.CV2021★ 343 cited
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
Zirui Wang, Jiahui Yu, Adams Wei Yu +3
With recent progress in joint modeling of visual and textual representations, Vision-Language Pretraining (VLP) has achieved impressive performance on many multimodal downstream ta…