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UniSlider: Perceptually Uniform Sliders for Continuous Image Editing

Paper recorded by Signals 4 on 2026-10-05 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-05 on arXiv · recorded by Signals 4 on 2026-10-06

Category: cs.AI · 人工智能 · first seen 2026-10-06

Abstract

Sliders provide an intuitive interface for continuous image editing. In current generative approaches, however, the slider is simply a rescaling of the method's strength parameter, such as an adapter coefficient, a prompt weight, or an interpolation factor. This strength relates poorly to perceptual change. The image can partially revert as the slider moves, long stretches of the range produce no

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#446 most recent of 980 cs.AI papers we have recorded · ↑ newer: Recursive Video In-Context Learning for Agentic Robot · ↓ older: MemPilot: Orchestrating On-Demand Multimodal Memory Curation for LLM A
Cite this page: UniSlider: Perceptually Uniform Sliders for Continuous Image Editing: the #446 most recent of 980 cs.AI papers we have recorded (as of 2026-10-05). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/unislider-perceptually-uniform-sliders-for-continuous-image-editing.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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