mlsanityData to 14 Oct 2026

Sequential Gallery for Interactive Visual Design Optimization

arXiv 2005.04107 ↗First posted 8 May 2020cs.GR cs.HC cs.LGcited by 25

Not on the map. Why?

Abstract (arXiv)

Visual design tasks often involve tuning many design parameters. For example, color grading of a photograph involves many parameters, some of which non-expert users might be unfamiliar with. We propose a novel user-in-the-loop optimization method that allows users to efficiently find an appropriate parameter set by exploring such a high-dimensional design space through much easier two-dimensional search subtasks. This method, called sequential plane search, is based on Bayesian optimization to keep necessary queries to users as few as possible. To help users respond to plane-search queries, we also propose using a gallery-based interface that provides options in the two-dimensional subspace arranged in an adaptive grid view. We call this interactive framework Sequential Gallery since users sequentially select the best option from the options provided by the interface. Our experiment with synthetic functions shows that our sequential plane search can find satisfactory solutions in fewer iterations than baselines. We also conducted a preliminary user study, results of which suggest that novices can effectively complete search tasks with Sequential Gallery in a photo-enhancement scenario.

Key facts. Cited by 25 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 May 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 4; 2022: 3; 2023: 6; 2024: 3; 2025: 5; 2026: 4.

25 papers.

Sort:

By area:

  1. 2023PromptPaint: Steering Text-to-Image Generation Through Paint Medium-like Interactionscited by 34
  2. 2023Looping in the Human Collaborative and Explainable Bayesian Optimizationcited by 27
  3. 2023Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processescited by 19
  4. 2023Active Learning and Bayesian Optimization: a Unified Perspective to Learn with a Goalcited by 17
  5. 2021Discovering Diverse Athletic Jumping Strategiescited by 16
  6. 2024Principled Preferential Bayesian Optimizationcited by 16
  7. 2022Toward Modeling Creative Processes for Algorithmic Paintingcited by 9
  8. 2025PABBO: Preferential Amortized Black-Box Optimizationcited by 8
  9. 2021Toward AI Assistants That Let Designers Designcited by 6
  10. 2022Investigating Positive and Negative Qualities of Human-in-the-Loop Optimization for Designing Interaction Techniquescited by 6
  11. 2021Efficient Hyperparameter Optimization for Physics-based Character Animationcited by 5
  12. 2022Efficient Human-in-the-loop System for Guiding DNNs Attentioncited by 4
13 more
  1. 2025Cooperative Design Optimization through Natural Language Interactioncited by 4
  2. 2021Tool- and Domain-Agnostic Parameterization of Style Transfer Effects Leveraging Pretrained Perceptual Metricscited by 2
  3. 2023Crowd-Powered Photo Enhancement Featuring an Active Learning Based Local Filtercited by 2
  4. 2025Efficient Visual Appearance Optimization by Learning from Prior Preferencescited by 2
  5. 2023The Impact of Expertise in the Loop for Exploring Machine Rationalitycited by 1
  6. 2024Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimizationcited by 1
  7. 2024SwipeGANSpace: Swipe-to-Compare Image Generation via Efficient Latent Space Explorationcited by 0
  8. 2025Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimizationcited by 0
  9. 2025LAPPI: Interactive Optimization with LLM-Assisted Preference-Based Problem Instantiationcited by 0
  10. 2026GimmBO: Interactive Generative Image Model Merging via Bayesian Optimizationcited by 0
  11. 2026Cost-Aware Bayesian Optimization for Prototyping Interactive Devicescited by 0
  12. 2026Adaptive Prompt Elicitation for Text-to-Image Generationcited by 0
  13. 2026Rethinking Opinion Measurement Interfaces for Human-in-the-Loop Optimizationcited by 0