mlsanityData to 7 Oct 2026

LightsOut: Diffusion-based Outpainting for Enhanced Lens Flare Removal

arXiv 2510.15868 ↗First posted 17 Oct 2025cs.CVcited by 9

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Abstract (arXiv)

Lens flare significantly degrades image quality, impacting critical computer vision tasks like object detection and autonomous driving. Recent Single Image Flare Removal (SIFR) methods perform poorly when off-frame light sources are incomplete or absent. We propose LightsOut, a diffusion-based outpainting framework tailored to enhance SIFR by reconstructing off-frame light sources. Our method leverages a multitask regression module and LoRA fine-tuned diffusion model to ensure realistic and physically consistent outpainting results. Comprehensive experiments demonstrate LightsOut consistently boosts the performance of existing SIFR methods across challenging scenarios without additional retraining, serving as a universally applicable plug-and-play preprocessing solution. Project page: https://ray-1026.github.io/lightsout/

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 63 of its 88 references that are in the map. First posted on arXiv 17 Oct 2025.

Builds on

63 of 88 references.

References · 63

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38 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 5.

9 papers.

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  1. 2025Physics-Informed Video Flare Synthesis and Removal Leveraging Motion Independence between Flare and Scene
  2. 2024Difflare: Removing Image Lens Flare with Latent Diffusion Model
  3. 2025DeflareMamba: Hierarchical Vision Mamba for Contextually Consistent Lens Flare Removal
  4. 2026Breaking Spatial Uniformity: Prior-Guided Mamba with Radial Serialization for Lens Flare Removal
  5. 2025DiffusionLight-Turbo: Accelerated Light Probes for Free via Single-Pass Chrome Ball Inpainting
  6. 2025Structure-Guided Diffusion Models for High-Fidelity Portrait Shadow Removal
  7. 2024Diff-Shadow: Global-guided Diffusion Model for Shadow Removal
  8. 2025Learning to See Through Flare