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 …

Generating a description of an image is called image captioning. Image captioning requires
recognizing the important objects, their attributes, and their relationships in an image. It also …

Recent progress on visual question answering has explored the merits of grid features for
vision language tasks. Meanwhile, transformer-based models have shown remarkable …

Attention mechanisms are widely used in current encoder/decoder frameworks of image
captioning, where a weighted average on encoded vectors is generated at each time step to …

Language understanding research is held back by a failure to relate language to the
physical world it describes and to the social interactions it facilitates. Despite the incredible …

Abstract We propose Scene Graph Auto-Encoder (SGAE) that incorporates the language
inductive bias into the encoder-decoder image captioning framework for more human-like …

Our experience of the world is multimodal-we see objects, hear sounds, feel texture, smell
odors, and taste flavors. Modality refers to the way in which something happens or is …

Image captioning aims to automatically generate a natural language description of a given
image, and most state-of-the-art models have adopted an encoder-decoder framework. The …

Attention-based neural encoder-decoder frameworks have been widely adopted for image
captioning. Most methods force visual attention to be active for every generated word …

This paper surveys the current state of the art in Natural Language Generation (NLG),
defined as the task of generating text or speech from non-linguistic input. A survey of NLG is …