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 latent-space reflection separation while leveraging the flash cues. Specifically, Flash-Split consists of two stages. Stage 1 separates apart the reflection latent and transmission latent via a dual-branch diffusion model conditioned on an encoded flash/no-flash latent pair, effectively mitigating the flash/no-flash misalignment issue. Stage 2 restores high-resolution, faithful details to the separated latents, via a cross-latent decoding process conditioned on the original images before separation. By validating Flash-Split on challenging real-world scenes, we demonstrate state-of-the-art reflection separation performance and significantly outperform the baseline methods.
@article{arxiv.2501.00637,
title = {Flash-Split: 2D Reflection Removal with Flash Cues and Latent Diffusion Separation},
author = {Tianfu Wang and Mingyang Xie and Haoming Cai and Sachin Shah and Christopher A. Metzler},
journal= {arXiv preprint arXiv:2501.00637},
year = {2025}
}