We introduce the first dataset for sequential vision-to-language, and explore how this data may be used for the task of visual storytelling. The dataset includes 81,743 unique photos in 20,211 sequences, aligned to descriptive and story language. VIST is previously known as "SIND", the Sequential Image Narrative Dataset (SIND).

The Visual Storytelling Dataset (VIST) consists of 10,117 Flickr albums and 210,819 unique images. Each sample is one sequence of 5 photos selected from the same album paired with a single human constructed story, where each story is comprised of mostly one sentence per image.

This directory contains the necessary files for the Artistic Visual Storytelling task. For a short dataset description, please, read the README.md.

Import note: The Artistic Visual Storytelling dataset can be used only for non-commercial academic research purposes.

If you use this dataset, please cite it as below:

Efthymiou, A.; Rudinac, S.; Kackovic, M.; Worring, M.; Wijnberg, N.M. (2023): Artistic Visual Storytelling. University of Amsterdam / Amsterdam University of Applied Sciences. Dataset. https://doi.org/10.21942/uva.20050970.v2

This version of the Bloom Library data is developed specifically for the Visual Story Telling (VIST) task. It includes data from 363 languages across 36 language families, with many of the languages represented being extremely low resourced languages.

Video Storytelling is a dataset for generating text story/summarization for videos containing social events. It consists of 105 videos from four categories: birthday, camping, Christmas and wedding. For each video, we provide at least 5 human-written stories.

• Videos are contained in the .tar file with their corresponding category name.
• Text stories are contained in Text.tar.
• In each txt file, the first line is the video id. The start and end time (in seconds) of each sentence is also given.
• test_id.txt provides the id for videos in the test set

Please cite the following paper if you use the Video Storytelling dataset in your work (papers, articles, reports, books, software, etc):

• Video Storytelling: Textual Summaries for Events. J. Li, Y. Wong, Q.Zhao, M. Kankanhalli. IEEE Transactions on Multimedia.

Visual storytelling refers to the manner of describing a set of images rather than a single image, also known as multi-image captioning. Visual Storytelling Task (VST) takes a set of images as input and aims to generate a coherent story relevant to the input images. In this dataset, we bridge the gap and present a new dataset for expressive and coherent story creation. We present the Sequential Storytelling Image Dataset (SSID), consisting of open-source video frames accompanied by story-like annotations. In addition, we provide four annotations (i.e., stories) for each set of five images. The image sets are collected manually from publicly available videos in three domains: documentaries, lifestyle, and movies, and then annotated manually using Amazon Mechanical Turk. In summary, SSID dataset is comprised of 17,365 images, which resulted in a total of 3,473 unique sets of five images. Each set of images is associated with four ground truths, resulting in a total of 13,892 unique ground truths (i.e., written stories). And each ground truth is composed of five connected sentences written in the form of a story.

Story maps have emerged as a popular storytelling device in recent years with cartographers and journalists leveraging geospatial web technologies to create unique spatial narratives. However, empirical research analyzing the design of story maps remains limited. Two recently proposed design frameworks provide promising avenues to characterize story maps in terms of elements of vivid cartography and techniques of map-based storytelling. In this article, I conducted a quantitative content analysis on 117 story maps of COVID-19 to operationalize map-based storytelling and vividness frameworks and to identify common design traits in contemporary story maps. My findings indicated that most story maps are longform infographics that use scrolling to advance the narrative. Stories applied a variety of attention, dosing, and mood techniques to enrich the storytelling experience. Story maps were primarily vivid through their use of color and novelty. Overall, most story maps utilized only a fraction of the map-based storytelling framework techniques. This research also demonstrated that it is challenging to analyze story maps based on these frameworks. Finally, this article improves the frameworks by proposing two new story map techniques and suggesting avenues of refinement.

Supporting data for the article "The Illustrated Page: Analyzing Illustrations of Historical Children’s Books Using Citizen Science" (CHR 2025)

Comprehensive analysis and strategic guide for mortgage lending professionals seeking to implement advanced content marketing strategies in 2025. This dataset provides detailed insights into video marketing, interactive content, visual storytelling, and specialized SEO techniques specifically tailored for the mortgage industry. The content addresses the evolution from generic blog posts to personalized, engaging content that builds trust with modern borrowers who expect authentic, helpful guidance through their home-buying journey.

Visual narratives are promising tools for science and health communication, especially for broad audiences in times of public health crisis, such as during the COVID-19 pandemic. In this study, we used the Lifeology illustrated “flashcard” course platform to construct visual narratives about COVID-19, and then assessed their impact on behavioral intentions. We conducted a survey experiment among 1,775 health app users. Participants viewed illustrated (sequential art) courses about: 1) sleep, 2) what COVID-19 is and how to protect oneself, 3) mechanisms of how the virus works in the body and risk factors for severe disease. Each participant viewed one of these courses and then answered questions about their understanding of the course, how much they learned, and their perceptions and behavioral intentions toward COVID-19. Participants generally evaluated “flashcard” courses as easy to understand. Viewing a COVID-19 “flashcard” course was also associated with improved self-efficacy and behavioral intentions toward COVID-19 disease prevention as compared to viewing a “flashcard” course about sleep science. Our findings support the use of visual narratives to improve health literacy and provide individuals with the capacity to act on health information that they may know of but find difficult to process or apply to their daily lives.

Discover the booming digital visual content market! This in-depth analysis reveals key trends, growth projections (CAGR), major players (Shutterstock, Getty Images, Adobe), and regional insights from 2019-2033. Learn about the driving forces and challenges shaping this multi-billion dollar industry.

In visual narratives like comics, the most overt form of perspective-taking comes in panels that directly depict the viewpoints of characters in the scene. We therefore examined these subjective viewpoint panels (also known as point-of-view panels) in a corpus of over 300 annotated comics from Asia, Europe, and the United States. In line with predictions that Japanese manga use a more “subjective” storytelling style than other comics, we found that more manga use subjective panels than other comics, with high proportions of subjective panels also found in Chinese, French, and American comics. In addition, panels with more “focal” framing, i.e. micro panels showing close ups and/or amorphic panels showing views of the environment, had higher proportions of subjective panels than panels showing wider views of scenes. These findings further show that empirical corpus analyses provide evidence of cross-cultural variation and reveal relationships across structures in the visual languages of comics.

The social media design app market is booming, projected to reach $701.3 million by 2033 with a 9.6% CAGR. Learn about key drivers, trends, and leading players like Canva and Adobe in this in-depth market analysis. Discover regional market shares and growth opportunities in this rapidly evolving sector.

This dataset is introduced by the paper "Understanding, Categorizing and Predicting Semantic Image-Text Relations". If you are using this dataset it in your work, please cite: @inproceedings{otto2019understanding, title={Understanding, Categorizing and Predicting Semantic Image-Text Relations}, author={Otto, Christian and Springstein, Matthias and Anand, Avishek and Ewerth, Ralph}, booktitle={In Proceedings of ACM International Conference on Multimedia Retrieval (ICMR 2019)}, year={2019} } To create the full tar use the following command in the command line: cat train.tar.part* > train_concat.tar Then simply untar it via tar -xf train_concat.tar The jsonl files contain metadata of the following format: id, origin, CMI, SC, STAT, ITClass, text, tagged text, image_path License Information: This dataset is composed of various open access sources as described in the paper. We thank all the original authors for their work. Pitt Image Ads Dataset: http://people.cs.pitt.edu/~kovashka/ads/ Image-Net challenge: http://image-net.org/ Visual Storytelling Dataset (VIST): http://visionandlanguage.net/VIST/ Wikipedia: https://www.wikipedia.org/ Microsoft COCO: http://cocodataset.org/#home

BLOOM VIST is a visual storytelling of books that consists of 62 languages indigenous to SEA. This dataset is owned by Bloom, a free, open-source software developed by SIL International and associated with Bloom Library, app, and services. This dataset is released with the LICENSE family of Creative Commons (although each story datapoints has its licensing in more detail, e.g cc-by, cc-by-nc, cc-by-nd, cc-by-sa, cc-by-nc-nd, cc-by-nc-sa). Before using this dataloader, please accept the… See the full description on the dataset page: https://huggingface.co/datasets/SEACrowd/bloom_vist.

Explore the booming Commercial Illustration market with key insights on drivers, trends, and segments. Discover growth opportunities in advertising, publishing, and entertainment.

Abstract This article is about the discourse on learning languages construed and transmitted by images in websites of private schools specialized in foreign languages teaching, evidencing the representations construed by these establishments to society. The argument favors the consideration of images in language studies, and the theoretical basis adopted includes the socio-semiotic approach to language, the Grammar of Visual Design, and the concept of social representation. The corpus analysis evidences the representation of the learning in optimal conditions of comfort, homogeneity, with the presence of resources and diverse instruments, in which the student is an agent of processes related to linguistic reception. It is concluded that these visual narratives contribute to the idea widely spread in society that the ideal language learning happens in private specialized schools and is reserved for few people.

Discover the booming digital storytelling platform market! Our analysis reveals a $3712 million market in 2025, growing at 7.8% CAGR through 2033. Learn about key drivers, trends, and top players like Adobe and Canva. Explore market segmentation and regional insights for informed business decisions.

DATABIRD VISUALS

  Description

This dataset contains 5755 entries focused on understanding color theory principles and their application in various fields including complimentary colors, working with color contrasts, color psychology, color and branding, color in fashion design, color grading and visual storytelling, associating colors with emotions, building a color palette, and the impact of black and white vs. color imagery. The data is provided in JSON format. Each… See the full description on the dataset page: https://huggingface.co/datasets/theprint/databird-visuals.