Flash-Split: 2D Reflection Removal with Flash Cues and Latent Diffusion Separation
Conference on Computer Vision and Pattern Recognition (CVPR) — 2025
Transparent surfaces, such as glass, create complex reflections that obscure images and challenge downstream computer vision applications. We introduce Flash-Split, a robust framework for separating transmitted and reflected light using a single (potentially misaligned) pair of flash/no-flash images. Our core idea is to perform flash-informed reflection separation iteratively in a low-dimensional latent space. Specifically, Flash-Split consists of two stages. Stage 1 separates the reflection latent and transmission latent via a dual-branch diffusion model that is conditioned on an encoded flash/no-flash latent pair. This stage effectively mitigates the flash/no-flash misalignment issue. Stage 2 restores high-resolution, faithful details to the separated latents via a cross-latent decoding process that is conditioned on the original images before separation. We validate Flash-Split on challenging real-world scenes and demonstrate it significantly outperforms existing methods.
@article{ Wang2025Flash-Split,
author = { Wang, Tianfu and Xie, Mingyang and Cai, Haoming and Shah, Sachin and Metzler, Christopher A. },
title = { Flash-Split: 2D Reflection Removal with Flash Cues and Latent Diffusion Separation },
journal = { Conference on Computer Vision and Pattern Recognition (CVPR) },
year = { 2025 },
}