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VLRM: Vision-Language Models act as Reward Models for Image Captioning
In this work, we present an unsupervised method for enhancing an image captioning model (in our case, BLIP2) using reinforcement learning and vision-language models like CLIP and BLIP2-ITM as reward models.
MDMMT-2: Multidomain Multimodal Transformer for Video Retrieval, One More Step Towards Generalization
In this work we present a new State-of-The-Art on the text-to-video retrieval task on MSR-VTT, LSMDC, MSVD, YouCook2 and TGIF obtained by a single model.
Ranked #1 on
Video Retrieval
on TGIF
(using extra training data)
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