In our digital age, data are generated constantly from public and private sources, social
media platforms, and the Internet of Things. A significant portion of this information comes in …

Current work on image-based story generation suffers from the fact that the existing image
sequence collections do not have coherent plots behind them. We improve visual story …

Visual storytelling is the task of generating a related story for a given image sequence, which
has received significant attention. However, using general RNNs (such as LSTM and GRU) …

Visual storytelling aims to automatically generate a human-like short story given an image
stream. Most existing works utilize either scene-level or object-level representations …

Visual storytelling aims to generate compelling narratives from image sequences. Existing
models often focus on enhancing the representation of the image sequence, eg, with …

The visual storytelling (VIST) task aims at generating reasonable, human-like and coherent
stories with the image streams as input. Although many deep learning models have …

Local coherence is essential for long-form text generation models. We identify two important
aspects of local coherence within the visual storytelling task:(1) the model needs to …

Data-driven storytelling is a powerful method for conveying insights by combining narrative
techniques with visualizations and text. These stories integrate visual aids, such as …

Characters are essential to the plot of any story. Establishing the characters before writing a
story can improve the clarity of the plot and the overall flow of the narrative. However …

We address the problem of visual storytelling, ie, generating a story for a given sequence of
images. While each story sentence should describe a corresponding image, a coherent …