4,369 research outputs found
A Survey for Graphic Design Intelligence
Graphic design is an effective language for visual communication. Using
complex composition of visual elements (e.g., shape, color, font) guided by
design principles and aesthetics, design helps produce more visually-appealing
content. The creation of a harmonious design requires carefully selecting and
combining different visual elements, which can be challenging and
time-consuming. To expedite the design process, emerging AI techniques have
been proposed to automatize tedious tasks and facilitate human creativity.
However, most current works only focus on specific tasks targeting at different
scenarios without a high-level abstraction. This paper aims to provide a
systematic overview of graphic design intelligence and summarize literature in
the taxonomy of representation, understanding and generation. Specifically we
consider related works for individual visual elements as well as the overall
design composition. Furthermore, we highlight some of the potential directions
for future explorations.Comment: 10 pages, 2 figure
AAAI 2008 Workshop Reports
AAAI was pleased to present the AAAI-08 Workshop Program, held Sunday and Monday, July 13-14, in Chicago, Illinois, USA. The program included the following 15 workshops: Advancements in POMDP Solvers; AI Education Workshop Colloquium; Coordination, Organizations, Institutions, and Norms in Agent Systems, Enhanced Messaging; Human Implications of Human-Robot Interaction; Intelligent Techniques for Web Personalization and Recommender Systems; Metareasoning: Thinking about Thinking; Multidisciplinary Workshop on Advances in Preference Handling; Search in Artificial Intelligence and Robotics; Spatial and Temporal Reasoning; Trading Agent Design and Analysis; Transfer Learning for Complex Tasks; What Went Wrong and Why: Lessons from AI Research and Applications; and Wikipedia and Artificial Intelligence: An Evolving Synergy
A survey of comics research in computer science
Graphical novels such as comics and mangas are well known all over the world.
The digital transition started to change the way people are reading comics,
more and more on smartphones and tablets and less and less on paper. In the
recent years, a wide variety of research about comics has been proposed and
might change the way comics are created, distributed and read in future years.
Early work focuses on low level document image analysis: indeed comic books are
complex, they contains text, drawings, balloon, panels, onomatopoeia, etc.
Different fields of computer science covered research about user interaction
and content generation such as multimedia, artificial intelligence,
human-computer interaction, etc. with different sets of values. We propose in
this paper to review the previous research about comics in computer science, to
state what have been done and to give some insights about the main outlooks
TextPainter: Multimodal Text Image Generation with Visual-harmony and Text-comprehension for Poster Design
Text design is one of the most critical procedures in poster design, as it
relies heavily on the creativity and expertise of humans to design text images
considering the visual harmony and text-semantic. This study introduces
TextPainter, a novel multimodal approach that leverages contextual visual
information and corresponding text semantics to generate text images.
Specifically, TextPainter takes the global-local background image as a hint of
style and guides the text image generation with visual harmony. Furthermore, we
leverage the language model and introduce a text comprehension module to
achieve both sentence-level and word-level style variations. Besides, we
construct the PosterT80K dataset, consisting of about 80K posters annotated
with sentence-level bounding boxes and text contents. We hope this dataset will
pave the way for further research on multimodal text image generation.
Extensive quantitative and qualitative experiments demonstrate that TextPainter
can generate visually-and-semantically-harmonious text images for posters.Comment: Accepted to ACM MM 2023. Dataset Link:
https://tianchi.aliyun.com/dataset/16003
Player agency in interactive narrative: audience, actor & author
The question motivating this review paper is, how can
computer-based interactive narrative be used as a constructivist learn-
ing activity? The paper proposes that player agency can be used to
link interactive narrative to learner agency in constructivist theory,
and to classify approaches to interactive narrative. The traditional
question driving research in interactive narrative is, āhow can an in-
teractive narrative deal with a high degree of player agency, while
maintaining a coherent and well-formed narrative?ā This question
derives from an Aristotelian approach to interactive narrative that,
as the question shows, is inherently antagonistic to player agency.
Within this approach, player agency must be restricted and manip-
ulated to maintain the narrative. Two alternative approaches based
on Brechtās Epic Theatre and Boalās Theatre of the Oppressed are
reviewed. If a Boalian approach to interactive narrative is taken the
conflict between narrative and player agency dissolves. The question
that emerges from this approach is quite different from the traditional
question above, and presents a more useful approach to applying in-
teractive narrative as a constructivist learning activity
Leveraging Large Models for Crafting Narrative Visualization: A Survey
Narrative visualization effectively transforms data into engaging stories,
making complex information accessible to a broad audience. Large models,
essential for narrative visualization, inherently facilitate this process
through their superior ability to handle natural language queries and answers,
generate cohesive narratives, and enhance visual communication. Inspired by
previous work in narrative visualization and recent advances in large models,
we synthesized potential tasks and opportunities for large models at various
stages of narrative visualization. In our study, we surveyed 79 papers to
explore the role of large models in automating narrative visualization
creation. We propose a comprehensive pipeline that leverages large models for
crafting narrative visualization, categorizing the reviewed literature into
four essential phases: Data, Narration, Visualization, and Presentation.
Additionally, we identify nine specific tasks where large models are applied
across these stages. This study maps out the landscape of challenges and
opportunities in the LM4NV process, providing insightful directions for future
research and valuable guidance for scholars in the field.Comment: 20 pages,6 figures, 2 table
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