research-article

Attribit: content creation with semantic attributes

Authors:

Siddhartha Chaudhuri,

Evangelos Kalogerakis,

Stephen Giguere,

Thomas FunkhouserAuthors Info & Claims

UIST '13: Proceedings of the 26th annual ACM symposium on User interface software and technology

Pages 193 - 202

https://doi.org/10.1145/2501988.2502008

Published: 08 October 2013 Publication History

Abstract

We present AttribIt, an approach for people to create visual content using relative semantic attributes expressed in linguistic terms. During an off-line processing step, AttribIt learns semantic attributes for design components that reflect the high-level intent people may have for creating content in a domain (e.g. adjectives such as "dangerous", "scary" or "strong") and ranks them according to the strength of each learned attribute. Then, during an interactive design session, a person can explore different combinations of visual components using commands based on relative attributes (e.g. "make this part more dangerous"). Novel designs are assembled in real-time as the strengths of selected attributes are varied, enabling rapid, in-situ exploration of candidate designs. We applied this approach to 3D modeling and web design. Experiments suggest this interface is an effective alternative for novices performing tasks with high-level design goals.

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Cited By

Zhou MZhang DYou WYu ZWu YPan CLiu HLao TChen P(2024)StyleFactory: Towards Better Style Alignment in Image Creation through Style-Strength-Based Control and EvaluationProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676370(1-15)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676370
Brade SWang BSousa MNewsome GOore SGrossman T(2024)SynthScribe: Deep Multimodal Tools for Synthesizer Sound Retrieval and ExplorationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645158(51-65)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645158
Yen YE JJin HLi MLin GPan IDow S(2024)ProcessGallery: Contrasting Early and Late Iterations for Design Principle LearningProceedings of the ACM on Human-Computer Interaction10.1145/36373898:CSCW1(1-35)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637389
Show More Cited By

Index Terms

Attribit: content creation with semantic attributes
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Shape inference
      2. Computer vision representations
        Shape representations
  2. Computer graphics
    1. Shape modeling
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms

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cover image ACM Conferences

UIST '13: Proceedings of the 26th annual ACM symposium on User interface software and technology

October 2013

558 pages

ISBN:9781450322683

DOI:10.1145/2501988

General Chairs:
Shahram Izadi
Microsoft Research, UK
,
Aaron Quigley
University of St Andrews, UK
,
Program Chairs:
Ivan Poupyrev
Disney Research, USA
,
Takeo Igarashi
The University of Tokyo, Japan

Copyright © 2013 ACM.

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Published: 08 October 2013

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UIST'13: The 26th Annual ACM Symposium on User Interface Software and Technology

October 8 - 11, 2013

St. Andrews, Scotland, United Kingdom

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UIST '13 Paper Acceptance Rate 62 of 317 submissions, 20%;

Overall Acceptance Rate 561 of 2,567 submissions, 22%

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The 38th Annual ACM Symposium on User Interface Software and Technology

September 28 - October 1, 2025

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Cited By

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https://dl.acm.org/doi/10.1145/3654777.3676370
Brade SWang BSousa MNewsome GOore SGrossman T(2024)SynthScribe: Deep Multimodal Tools for Synthesizer Sound Retrieval and ExplorationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645158(51-65)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645158
Yen YE JJin HLi MLin GPan IDow S(2024)ProcessGallery: Contrasting Early and Late Iterations for Design Principle LearningProceedings of the ACM on Human-Computer Interaction10.1145/36373898:CSCW1(1-35)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637389
Wang ZHuang YSong DMa LZhang T(2024)PromptCharm: Text-to-Image Generation through Multi-modal Prompting and RefinementProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642803(1-21)Online publication date: 11-May-2024
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Oh JKim SKim S(2024)LumiMood: A Creativity Support Tool for Designing the Mood of a 3D SceneProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642440(1-21)Online publication date: 11-May-2024
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Petrov DGadelha MMěch RKalogerakis E(2024)ANISE: Assembly-Based Neural Implicit Surface ReconstructionIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.326530630:8(4514-4526)Online publication date: Aug-2024
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Zhang LLi ZZheng Y(2024)An interactive generative design technology for appearance diversity – Taking mouse design as an exampleAdvanced Engineering Informatics10.1016/j.aei.2023.10226359(102263)Online publication date: Jan-2024
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Chen YWang TWu TPan XJia KLiu Z(2024)ComboVerse: Compositional 3D Assets Creation Using Spatially-Aware Diffusion GuidanceComputer Vision – ECCV 202410.1007/978-3-031-72691-0_8(128-146)Online publication date: 3-Nov-2024
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