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Jean-Peïc Chou

dblp:356/3776 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2026
0009-0001-8381-7686ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 3 · 1 first-author · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
2 papers
User interface design and tools · 68% Human-AI interaction · 32%
Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 100%
Databases, data mining, and information retrieval
1 paper
Knowledge graphs · 100%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
User interface design and tools
visualization
0.812024
ScriptViz: A Visualization Tool to Aid Scriptwriting based on a Large Movie Database · UIST 2024
Human-AI interaction › AI-assisted writing
creative writing support
0.712023
TaleStream: Supporting Story Ideation with Trope Knowledge · UIST 2023
Multimedia analysis and retrieval › video retrieval
movie database retrieval
0.212024
ScriptViz: A Visualization Tool to Aid Scriptwriting based on a Large Movie Database · UIST 2024

Methods — techniques the papers use, named apart from their topics

visual reference retrieval · 1.5text retrieval · 1.5wiki data mining · 1.3trope suggestion · 1.3
YearPublicationVenuePosition
2026 CapSmith: Contextual Refinement of Additive Text Captions for Video Storytelling
Saehui Hwang, Jean-Peïc Chou, Anh Truong
Creativity & Cognition2
2024 ScriptViz: A Visualization Tool to Aid Scriptwriting based on a Large Movie Database
abstract
Scriptwriters usually rely on their mental visualization to create a vivid story by using their imagination to see, feel, and experience the scenes they are writing. Besides mental visualization, they often refer to existing images or scenes in movies and analyze the visual elements to create a certain mood or atmosphere. In this paper, we develop ScriptViz to provide external visualization based on a large movie database for the screenwriting process. It retrieves reference visuals on the fly based on scripts’ text and dialogue from a large movie database. The tool provides two types of control on visual elements that enable writers to 1) see exactly what they want with fixed visual elements and 2) see variances in uncertain elements. User evaluation among 15 scriptwriters shows that ScriptViz is able to present scriptwriters with consistent yet diverse visual possibilities, aligning closely with their scripts and helping their creation.
Anyi Rao, Jean-Peïc Chou, Maneesh Agrawala
UIST2
2023 TaleStream: Supporting Story Ideation with Trope Knowledge
abstract
Story ideation is a critical part of the story-writing process. It is challenging to support computationally due to its exploratory and subjective nature. Tropes, which are recurring narrative elements across stories, are essential in stories as they shape the structure of narratives and our understanding of them. In this paper, we propose to use tropes as an intermediate representation of stories to approach story ideation. We present TaleStream, a canvas system that uses tropes as building blocks of stories while providing steerable suggestions of story ideas in the form of tropes. Our trope suggestion methods leverage data from the tvtropes.org wiki. We find that 97% of the time, trope suggestions generated by our methods provide better story ideation materials than random tropes. Our system evaluation suggests that TaleStream can support writers’ creative flow and greatly facilitates story development. Tropes, as a rich lexicon of narratives with available examples, play a key role in TaleStream and hold promise for story-creation support systems.
Jean-Peïc Chou, Alexa F. Siu, Nedim Lipka, Ryan Rossi, Franck Dernoncourt, Maneesh Agrawala
UIST1