EdgeRelight360: Text-Conditioned 360-Degree HDR Image Generation for Real-Time On-Device Video Portrait Relighting
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Abstract (arXiv)
In this paper, we present EdgeRelight360, an approach for real-time video portrait relighting on mobile devices, utilizing text-conditioned generation of 360-degree high dynamic range image (HDRI) maps. Our method proposes a diffusion-based text-to-360-degree image generation in the HDR domain, taking advantage of the HDR10 standard. This technique facilitates the generation of high-quality, realistic lighting conditions from textual descriptions, offering flexibility and control in portrait video relighting task. Unlike the previous relighting frameworks, our proposed system performs video relighting directly on-device, enabling real-time inference with real 360-degree HDRI maps. This on-device processing ensures both privacy and guarantees low runtime, providing an immediate response to changes in lighting conditions or user inputs. Our approach paves the way for new possibilities in real-time video applications, including video conferencing, gaming, and augmented reality, by allowing dynamic, text-based control of lighting conditions.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 22 of its 46 references that are in the map. First posted on arXiv 15 Apr 2024.
Builds on
22 of 46 references.
References · 22
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10 more
- 2019Learning Physics-guided Face Relighting under Directional Lightcited by 90
- 2022Learning to Relight Portrait Images via a Virtual Light Stage and Synthetic-to-Real Adaptationcited by 67
- 2019Deep Sky Modeling for Single Image Outdoor Lighting Estimationcited by 66
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- 2022Face Relighting with Geometrically Consistent Shadowscited by 43
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- 2023ReliTalk: Relightable Talking Portrait Generation from a Single Videocited by 12
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Built on by
Citing papers per year: 2025: 4; 2026: 1.
5 papers.
- 2025Lux Post Facto: Learning Portrait Performance Relighting with Conditional Video Diffusion and a Hybrid Datasetcited by 28
- 2025VidCRAFT3: Camera, Object, and Lighting Control for Image-to-Video Generationcited by 25
- 2025Lumen: Consistent Video Relighting and Harmonious Background Replacement with Video Generative Modelscited by 13
- 2025Total-Editing: Head Avatar with Editable Appearance, Motion, and Lightingcited by 2
- 2026FusionRelight: Relighting Portraits in Real Time via Hybrid Domain Knowledge Fusioncited by 0
- 2026FusionRelight: Relighting Portraits in Real Time via Hybrid Domain Knowledge Fusion25 Apr 2026
- 2025Lumen: Consistent Video Relighting and Harmonious Background Replacement with Video Generative Models18 Aug 2025
- 2025Total-Editing: Head Avatar with Editable Appearance, Motion, and Lighting26 May 2025
- 2025Lux Post Facto: Learning Portrait Performance Relighting with Conditional Video Diffusion and a Hybrid Dataset18 Mar 2025
- 2025VidCRAFT3: Camera, Object, and Lighting Control for Image-to-Video Generation11 Feb 2025
Similar, not cited
Close in wording, no citation either way
- 2026Pixel Cube: Diffusion-based Portrait Video Relighting Through Realistic Lighting Reproduction
- 2026Video Generation Models Are Inherent Lighting Estimators
- 2024LumiSculpt: Enabling Consistent Portrait Lighting in Video Generation
- 2025RelightMaster: Precise Video Relighting with Multi-plane Light Images
- 2026LiveLight: Real-time Streaming Video Relighting with Interactive Control
- 2026CamLit: Unified Video Diffusion with Explicit Camera and Lighting Control
- 2025RelightVid: Temporal-Consistent Diffusion Model for Video Relighting
- 2026LightCtrl: Training-free Controllable Video Relighting