Connecting Vision and Language plays an essential role in Generative Intelligence. For this
reason, large research efforts have been devoted to image captioning, ie describing images …

Image captioning refers to automatic generation of descriptive texts according to the visual
content of images. It is a technique integrating multiple disciplines including the computer …

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 …

Modern image captioning models are usually trained with text similarity objectives. However,
since reference captions in public datasets often describe the most salient common objects …

Effectively aligning with human judgment when evaluating machine-generated image
captions represents a complex yet intriguing challenge. Existing evaluation metrics like …

Advances in the field of visual-language contrastive learning have made it possible for many
downstream applications to be carried out efficiently and accurately by simply taking the dot …

Despite the success of various text generation metrics such as BERTScore, it is still difficult
to evaluate the image captions without enough reference captions due to the diversity of the …

Current metrics for video captioning are mostly based on the text-level comparison between
reference and candidate captions. However, they have some insuperable drawbacks, eg …

Text-to-image generation and image captioning are recently emerged as a new
experimental paradigm to assess machine intelligence. They predict continuous quantity …

Establishing an automatic evaluation metric that closely aligns with human judgments is
essential for effectively developing image captioning models. Recent data-driven metrics …