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Found 3 papers, 3 papers with code
With a Little Help from your own Past: Prototypical Memory Networks for Image Captioning
Image captioning, like many tasks involving vision and language, currently relies on Transformer-based architectures for extracting the semantics in an image and translating it into linguistically coherent descriptions.
Positive-Augmented Contrastive Learning for Image and Video Captioning Evaluation
The CLIP model has been recently proven to be very effective for a variety of cross-modal tasks, including the evaluation of captions generated from vision-and-language architectures.
CaMEL: Mean Teacher Learning for Image Captioning
Describing images in natural language is a fundamental step towards the automatic modeling of connections between the visual and textual modalities.
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