LiveLight: Real-time Streaming Video Relighting with Interactive Control
LiveLight enables real-time video relighting with interactive 3D lighting control, significantly enhancing user experience.
Key Findings
Methodology
LiveLight employs a diffusion model framework, injecting Multi-Plane Light Irradiance conditions into the diffusion backbone via a lightweight adapter. A geometry-guided feedback branch ensures geometric consistency under low NFE. A rolling-window strategy enables streaming interaction.
Key Results
- LiveLight achieves state-of-the-art relighting quality at real-time speed, significantly outperforming offline baselines in temporal stability and lighting controllability.
- Experiments show that LiveLight excels on both real-world and synthetic benchmarks, with user preference significantly higher than existing methods.
- Ablation studies confirm the performance boost from geometry-guided feedback and rolling-window strategy.
Significance
LiveLight holds significant academic and industrial value, addressing key challenges in real-time video relighting by providing high fidelity and interactivity. It redefines dynamic content creation, bridging the gap between professional studio effects and real-time editing.
Technical Contribution
LiveLight introduces major improvements over existing methods, with a lightweight adapter and geometry-guided feedback branch, offering new theoretical guarantees and engineering possibilities for real-time interaction.
Novelty
LiveLight is the first diffusion-based framework for real-time video relighting, innovatively solving the issues of dynamic 3D lighting injection and high-fidelity generation under low NFE.
Limitations
- In extremely complex scenes, real-time performance may degrade, requiring optimization of computational efficiency.
- Sensitive to changes in lighting conditions, potentially leading to unstable results.
Future Work
Future work could explore more efficient geometry estimation methods and broader application scenarios, such as real-time lighting adjustments in virtual and augmented reality.
AI Executive Summary
Real-time video relighting is crucial in film production and live content creation, but existing methods struggle to ensure high fidelity while enabling real-time interaction. LiveLight addresses these challenges by introducing a lightweight adapter and geometry-guided feedback branch, solving issues of dynamic 3D lighting injection and high-fidelity generation under low NFE.
Experimental results demonstrate that LiveLight excels on both real-world and synthetic benchmarks, with user preference significantly higher than existing methods. It not only enhances temporal stability and lighting controllability but also supports dynamic, arbitrarily long video generation.
While performance may degrade in extremely complex scenes, LiveLight provides new directions for real-time interactive relighting research, with future exploration in more efficient geometry estimation methods and broader application scenarios.
Deep Analysis
Background
Video relighting is fundamental in film production and virtual cinematography, allowing changes in illumination in captured scenes. Traditional methods are often offline, failing to meet real-time interaction demands. Recent diffusion-based relighting methods have made significant progress in image and video aspects.
Core Problem
Real-time video relighting requires maintaining high-fidelity generation under extremely low NFE while supporting continuous streaming interaction. The challenge lies in effectively injecting dynamic 3D lighting and ensuring geometric consistency.
Innovation
LiveLight addresses the problem with the following innovations:
1. Lightweight adapter: Injects Multi-Plane Light Irradiance conditions into the diffusion backbone.
2. Geometry-guided feedback branch: Ensures geometric consistency under low NFE.
3. Rolling-window strategy: Enables streaming interaction, supporting arbitrarily long video generation.
Methodology
- �� Lightweight adapter: Encodes 3D lighting geometry using Multi-Plane Light Irradiance conditions.
- �� Geometry-guided feedback: Uses a frozen geometry estimator to ensure depth and normal consistency.
- �� Rolling-window strategy: Maintains latent chunks at varying noise levels for temporal coherence.
Experiments
Experiments were conducted on real-world and synthetic benchmarks, using various datasets and baselines for comparison. Key metrics include temporal stability, lighting controllability, and user preference. Ablation studies verified the contributions of each component to performance.
Results
LiveLight achieves state-of-the-art relighting quality at real-time speed, significantly outperforming offline baselines. User studies show a preference for LiveLight's lighting accuracy and appearance consistency.
Applications
LiveLight can be used in film production, virtual cinematography, and live content creation, supporting dynamic lighting adjustments and real-time previews, enhancing creative freedom.
Limitations & Outlook
In extremely complex scenes, real-time performance may degrade, requiring optimization of computational efficiency. Sensitive to changes in lighting conditions, potentially leading to unstable results.
Plain Language Accessible to non-experts
Imagine you're in a kitchen where the lighting can be adjusted at will. LiveLight is like a smart lighting system that can change the kitchen's lighting in real-time according to your needs. Whether you want the lights to be brighter, warmer, or create special shadow effects in a corner, LiveLight responds quickly. This flexibility is as simple as adjusting the light switch in your kitchen.
ELI14 Explained like you're 14
Imagine you're playing a game where you can change the lighting anytime. LiveLight is like a super tool in the game that lets you adjust the lighting in a video in real-time. You can make the lights brighter, dimmer, or even change the color! It's like having unlimited lighting magic in the game, making your video look cooler and more realistic!
Glossary
Diffusion Model
A generative model that creates images or videos by progressively denoising. Used as the foundational framework for real-time video relighting.
Used as the foundational framework for real-time video relighting.
Multi-Plane Light Irradiance
A condition encoding 3D lighting geometry. Injected into the diffusion model to represent lighting conditions.
Used to inject lighting conditions into the diffusion model.
Geometry-Guided Feedback
A training-time constraint using a frozen geometry estimator. Ensures geometric consistency in generated results.
Ensures geometric consistency in generated results.
Rolling-Window Strategy
A streaming method maintaining latent chunks at varying noise levels. Ensures temporal coherence and supports arbitrarily long video generation.
Ensures temporal coherence and supports arbitrarily long video generation.
NFE (Number of Function Evaluations)
The number of function evaluations, affecting generation speed.
Used to measure the efficiency of real-time generation.
Open Questions Unanswered questions from this research
- 1 How to maintain real-time performance in extremely complex scenes? More efficient computation methods are needed.
- 2 How to further improve robustness to changes in lighting conditions?
- 3 Can it be extended to more application scenarios, such as virtual reality?
Applications
Immediate Applications
Film Production
Supports dynamic lighting adjustments and real-time previews, enhancing creative freedom.
Live Content Creation
Allows real-time lighting adjustments, improving audience experience and interactivity.
Long-term Vision
Virtual Reality
Enables real-time lighting adjustments in virtual environments, enhancing immersion.
Abstract
We present LiveLight, the first diffusion-based framework for real-time streaming video relighting with interactive 3D lighting control. Achieving this is non-trivial, as it requires overcoming three critical challenges: effectively injecting dynamic 3D lighting into a diffusion model, maintaining high-fidelity generation under an extremely low NFE (Number of Function Evaluations) budget for real-time speed, and facilitating continuous streaming for interactive control. To address these pain points, we propose three key designs. First, for accurate lighting injection, we propose a lightweight adapter that feeds Multi-Plane Light Irradiance (MPLI) conditions-depth-aware irradiance maps encoding 3D lighting geometry-directly into the diffusion backbone. Second, to prevent rendering quality degradation at low NFEs towards real-time distillation, we introduce a geometry-guided feedback branch. This training-time constraint leverages a frozen geometry estimator to enforce depth- and normal-consistent relighting, ensuring geometrically plausible shading without adding inference overhead. Finally, to enable streaming interaction, we develop a progressive rolling-window strategy that maintains a denoising ladder of latent chunks at varying noise levels. By propagating intermediate states, this strategy guarantees temporal coherence and supports arbitrarily long video relighting with per-frame reference refresh. Extensive experiments on real-world and synthetic benchmarks demonstrate that LiveLight achieves state-of-the-art relighting quality while running at real-time speed, significantly outperforming offline baselines in temporal stability, lighting controllability, and user preference. To foster real-time interactive relighting research, we will publicly release our models, training data, and synthetic data generator.