The Visual Storytelling Dataset (VIST) consists of 210,819 unique photos and 50,000 stories. The images were collected from albums on Flickr. The albums included 10 to 50 images and all the images in an album are taken in a 48-hour span. The stories were created by workers on Amazon Mechanical Turk, where the workers were instructed to choose five images from the album and write a story about them. Every story has five sentences, and every sentence is paired with its appropriate image. The dataset is split into 3 subsets, a training set (80%), a validation set (10%) and a test set (10%). All the words and interpunction signs in the stories are separated by a space character and all the location names are replaced with the word location. All the names of people are replaced with the words male or female depending on the gender of the person.

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

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.

The Creative Visual Storytelling Anthology is a collection of 100 author responses to an improved creative visual storytelling exercise over a sequence of three images. Each item contains four facet entries, corresponding to Entity, Scene, Narrative, and Title.

The Creative Visual Storytelling Anthology was collected on Amazon Mechanical Turk. Five different authors performed the task for 20 different Flickr and Search-and-Rescue image-sets ( a sequence of 3 images) for a total of 100 items in the anthology. There are 300 unique Entity and Scene entries (single-image facets completed for each image), 200 unique Narrative entries (multi-image facets performed twice with two and then three images), and 100 unique Title entries (multi-image facets completed for three images). Thus, with each one assigned a title, there are 100 unique stories in the anthology all together.

One set of images used in collecting the anthology originated from Flickr, under Creative Commons Licenses. We chose a subset of Huang et al’s VIST dataset and downselected their image sequences from five to three images to scaffold the Aristotelian dramatic structure. We do not release the Flickr images in order to track the providence of the images. The Flickr images' authors and copyright information and usage are documented in the Flickr imageset license spreadsheet.

The second source of images came from a Search and Rescue (SAR) scenario. We selected three images in-order from experimental runs from a human-robot collaboration task, and similar sequential images were excluded for sake of diversity. The SAR images can be obtained through the SCOUT (The Situated Corpus of Understanding Transactions) dataset.

A new dataset describing textual stories for events.

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.

Exploring visual storytelling is a book. It was written by Brian Arnold and published by Thomson Delmar Learning in 2007.

Visual and digital storytelling methods can reposition research participants as coproducers of knowledge, foster engagement and collaboration with marginalized peoples, and offer greater depth of self-expression. However, these methods are constituted in complex terrains of power. Without continual attenuation to power imbalances, the methods will contribute to the silencing and erasure of marginalized communities. This study outlines how reflexivity as a methodological tool and part of the Cultured-Centered Approach can enable the interrogation of terrains of power, allowing for the continual opening of democratic possibilities and community ownership of visual and digital storytelling infrastructures. Excerpts from the “Poverty Is Not Our Future” campaign illustrate the argument. The campaign's cocreated audio-visual advertisements communicate everyday stories of poverty among residents living in a poor suburban site in Auckland, Aotearoa New Zealand, and serve as a visual narrative of resistance to dominant structures. This study contributes to critical theorizing of culture and communication and the coconstruction of visual stories.

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 Story-Telling dataset (VIST) is the only publicly accessible dataset for storytelling problems. It comprises 210,819 distinct images that can be found in 10,117 different albums on Flickr and is arranged in sets of five different images.

Intelligent Grimm - Open-ended Visual Storytelling via Latent Diffusion Models (CVPR 2024)

This is the StorySalon dataset proposed in StoryGen. For the open-source PDF data, you can directly download the frames, corresponding masks, descriptions and original story narratives. For the data extracted from YouTube videos, we also provide their corresponding masks, descriptions and original story narratives in this repository. However, you need to refer to… See the full description on the dataset page: https://huggingface.co/datasets/haoningwu/StorySalon.

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Digital Storytelling Courses Market Size 2024-2028

The digital storytelling courses market size is forecast to increase by USD 267.84 million at a CAGR of 9.87% between 2023 and 2028. The market is experiencing significant growth due to several key trends. The increasing focus on enhancing soft skills in the workforce is driving demand for digital storytelling courses. These skills are essential for effective communication and engagement in various industries, including marketing, education, and healthcare. Additionally, the rising adoption of smart classrooms and the integration of technology in education are creating opportunities for digital storytelling courses. Furthermore, the rise in demand for Massive Open Online Courses (MOOCs) is providing learners with flexible and affordable access to high-quality digital storytelling training. These trends are expected to continue fueling market growth in the coming years.

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The market is experiencing significant growth as businesses recognize the value of effective communication through digital content. Online learning platforms are increasingly offering digital storytelling courses to help individuals and institutional learners develop multimedia stories using character development, plot, dialogue, and user-friendly storytelling approaches. These courses cover various aspects of digital communications, including soft skills, CRM, brand positioning, and K-12 interactive learning. Advanced digital storytelling courses incorporate multimedia development, artificial intelligence, augmented reality, and virtual reality to create personalized learning experiences. Historical documentaries and personal narratives are popular genres, while K-12 education and pre-K-12 education are significant markets. Corporate training also benefits from digital storytelling courses to enhance employee engagement and improve communication skills. Both degree and non-degree programs, as well as certification options, are available to cater to various learning needs.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.

Type

  Degree
  Non-degree
  certification


End-user

  Institutional learners
  Individual learners


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC

    China


  Middle East and Africa



  South America

By Type Insights

The degree segment is estimated to witness significant growth during the forecast period. In the rapidly evolving digital landscape, the demand for digital storytelling skills is on the rise. Online learning platforms have emerged as a popular choice for individuals and institutions seeking to master multimedia development and user-friendly storytelling approaches. Digital content creation encompasses various elements such as character development, plot, dialogue, and communication. Digital communications have transformed the way we learn and engage, with the integration of Artificial Intelligence, Augmented Reality, and Virtual Reality providing personalized learning experiences. Corporate training, advertising, brand building, content marketing, and higher education sectors are leveraging digital storytelling for enhancing user experience and engagement. Personalized narratives, educational videos, interactive games, website design, audio engineering, animation, and soft skills training are integral components of digital storytelling education.

Furthermore, the corporate sector, K12 interactive learning, and degree and non-degree programs are adopting digital storytelling to cater to the needs of institutional learners and individual learners. Traditional classrooms are evolving to incorporate digital raconteurs, with a focus on CRM, brand positioning, and user experience design. The IT sector, with its vast job opportunities, is driving the adoption of digital storytelling tools and techniques. Employees in senior management roles are seeking training to stay informed about the latest market trends and technologies. In summary, digital storytelling education is a crucial investment for individuals and organizations seeking to excel in the digital communications era. It encompasses various multimedia development techniques and user-centric approaches and is applicable across various sectors, including corporate training, advertising, brand building, content marketing, higher education, and K12 interactive learning.

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The Degree segment was valued at USD 291.78 million in 2018 and showed a gradual increase during the forecast period.

Regional Insights

North America is estimated to contribute 39% to the growth of the

This dataset is about book series and is filtered where the books is Production design for screen : visual storytelling in film and television. It has 10 columns such as book series, earliest publication date, latest publication date, average publication date, and number of authors. The data is ordered by earliest publication date (descending).

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.

Using data sourced from an independent sample of 2,950,625 people from X, Reddit, Quora, Threads and TikTok worldwide to September 9th, 2024, we gain better insights into storytelling's impact on film and video marketing. 42.1% of over 4.4 million respondents indicated they use storytelling in their work, citing visual storytelling as the form they are most reliant on. Read more.

Visual Content Market Outlook

The global visual content market size was valued at approximately USD 38 billion in 2023 and is projected to reach around USD 72 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.1% during the forecast period. This remarkable growth can be attributed to the increasing demand for engaging and interactive content across various platforms and the proliferation of digital channels. As businesses and content creators strive to capture the attention of increasingly distracted audiences, the importance of visual storytelling has never been more pronounced. Key growth factors include advances in digital technology, the rise of social media platforms, and an increasing preference for video content among consumers.

One of the primary growth drivers for the visual content market is the rapid technological advancements in digital imaging and video creation. With the advent of high-resolution cameras, drones, and sophisticated editing software, the quality of visual content has significantly improved, enabling creators to produce stunning visuals that captivate audiences. Additionally, the increasing penetration of smartphones and internet connectivity has democratized access to visual content creation tools, allowing anyone with a smartphone to create high-quality visual content. This democratization has led to an explosion of user-generated content, further fueling the demand for platforms and services that can manage, distribute, and monetize this content effectively.

The rise of social media as a dominant force in communication and marketing has also played a crucial role in propelling the visual content market. Platforms like Instagram, TikTok, and YouTube have become indispensable tools for brands aiming to reach a younger, more visually-oriented audience. These platforms thrive on visual content, and their algorithms often prioritize such content over text-based posts. In response, brands and businesses are increasingly investing in the creation of visual content to enhance their digital presence and engage with their audience more effectively. This shift towards visual-centric content strategies has created a burgeoning demand for both professional content creators and digital marketing specialists skilled in visual storytelling.

The increasing importance of visual content in e-learning and remote education is another factor contributing to market growth. As educational institutions and corporate training programs pivot towards online platforms, there is a growing need for engaging educational content that can be accessed remotely. Visual content, such as infographics, video lectures, and interactive presentations, has proven to be highly effective in capturing learners' attention and enhancing comprehension. This trend is expected to continue, especially with the ongoing digital transformation in education and corporate sectors. As a result, there is a significant opportunity for educational content creators and technology providers to expand their offerings in this space.

Regionally, North America remains a significant player in the visual content market, driven by a robust media and entertainment industry, high internet penetration, and a mature digital landscape. However, Asia Pacific is expected to witness the highest growth rate during the forecast period, driven by the rapid adoption of digital technologies, increasing internet users, and a burgeoning middle class with rising disposable incomes. Countries like China and India are at the forefront of this growth, with their large populations and fast-growing digital ecosystems. In Europe, the market is driven by the demand for high-quality content in advertising and corporate communication. Meanwhile, regions like Latin America and the Middle East & Africa are also showing promising growth, although from a smaller base, as they continue to enhance their digital infrastructure and consumer base.

Type Analysis

The visual content market is segmented by type into images, videos, infographics, presentations, and others. Images continue to be a fundamental aspect of the market, providing a wide array of applications across different sectors. High-quality images are crucial in advertising, social media marketing, and even e-commerce, where product images can significantly influence purchase decisions. With the advent of image recognition technologies and AI-driven editing tools, the creation and application of images have become more sophisticated, allowing for personalized content that can engage audiences more effectively. The growing trend of personalized marketing is further driving the demand for i

This dataset includes responses from 51 students who participated in a survey evaluating a short film used in Computer Science education, that portrayed three algorithmic approaches: ad-hoc, greedy, and dynamic programming. Using a 7-point Likert scale (-3 to 3), students rated statements about the film's characteristics and potential benefits. The questionnaire aimed to thoroughly capture students' perspectives on the film's attributes and educational impact.Items used in the survey.EF.Entertainment - The short film provided a high entertainment value.EF.ProductionValue - The short film had a high production value.EF.Premise - The premise (escape room) was intriguing.EF.Expressive - The short film was expressive.EF.Immersive - The short film was immersive.EF.Creative - The short film was creative.EF.Pacing The pacing of the story was appropriate.FA.Story-plot - I appreciate as important the presence of the story-plot.FA.LiveAction - I appreciate as important the use of live-action performances.FA.CameraWork - I appreciate as important the cut and switch of camera angles.FA.Atmosphere - I appreciate as important the mood and atmosphere.FA.Choreography - I appreciate as important the choreography.FA.Cinematography - I appreciate as important the depicted cinematography.FA.NonVerbal - I appreciate as important the facial expressions, body language of the actors.FA.SoundDesign I appreciate as important the sound design, narration and sound effects present.CB.Educational. The short film provided a high educational value.CB.Understanding The learning experience deepened my understanding of the subject.CB.Clarity The algorithmic strategies were clearly depicted.EB.Attention - The movie engaged my attention.EB.Curiosity - The movie engaged my curiosity.PU.Quicker - Using such short films during a class would enable me to learn and deepen algorithmic concepts more quickly.PU.Performance - Using such short films during a class would improve my learning performance and grades.PU.Efficiency - Using such short films could help me get the most out of my time while learning.PU.Knowledge - Using such short films may improve my knowledge.PU.Easier - Using such short films would make it easier to accomplish my learning tasks.PU.Overall Using such short films would be overall beneficial.PE.Enjoyable - The learning experience was enjoyable.PE.Exciting - The learning experience was exciting.PE.Pleasant - The learning experience was pleasant.PE.Interesting - The learning experience was interesting.PE.Immersive - The learning experience was immersive.C.Changes - The use of such short films may imply major changes in how I learn.C.Incorporation - It would be easy to incorporate such short films in my learning process.A.Worthwhile - Using similar educational short films to learn algorithmic concepts is a good idea.A.Positivity - I am positive towards using visual media to better understand algorithmic concepts.A.Appreciate - I would appreciate the availabilty of similar short films as learning instuments.A.WouldUse - If available, I would use such short films in my learning process.Eval.Use - I often use/used existing AlgoRythmics videos in my learning process.Eval.Comp - Overall, the short film approach (story-line, live-acting etc.) provides a richer and more valuable learning experience than the viewing of simple videos or animations.

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.

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.