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HELIOS system enables continuous outdoor urban scene relighting without paired data

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced HELIOS, a new image relighting approach designed to transform outdoor urban scenes from nighttime to daytime and vice versa. Unlike previous methods that required paired images or synthetic data, HELIOS utilizes unlabeled real-world datasets. It employs an albedo-based conditioning within a cycle-consistent diffusion pipeline to ensure accurate domain translation and prevent identity collapse. The system also incorporates a novel control mechanism using GPS-derived solar angles for continuous lighting manipulation, demonstrating superior performance in user studies compared to existing techniques. AI

IMPACT Enables more realistic and controllable manipulation of visual data for applications in autonomous driving and content creation.

RANK_REASON The cluster contains a research paper detailing a new method for image relighting. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

HELIOS system enables continuous outdoor urban scene relighting without paired data

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The cluster contains a research paper detailing a new method for image relighting. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Hala Djeghim, Nathan Piasco, Luis Rold\~ao, Moussab Bennehar, Dzmitry Tsishkou, C\'eline Loscos, D\'esir\'e Sidib\'e ·

    HELIOS: From midnight to noon, continuous outdoor urban scene relighting

    arXiv:2609.00901v1 Announce Type: new Abstract: Modifying the illumination of driving images is a fundamental challenge, as most datasets are captured at specific times of day. Existing methods rely on synthetic data or paired multi-illumination supervision, which limits their ge…

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