仅用一步推理实现快速图像翻译，支持多种视觉任务。
LBM: Latent Bridge Matching for Fast Image-to-Image Translation
- 在隐空间通过桥接匹配实现跨图像翻译
- 单步推理达到当前最佳性能
- 适用于去物、深度估计、光影控制等场景
本文提出一种名为隐空间桥接匹配（Latent Bridge Matching, LBM）的新方法，基于隐空间中的桥接匹配机制，实现高效且通用的图像到图像翻译。该方法仅需一次推理即可在多种图像翻译任务中达到前沿性能，包括物体移除、法向量与深度估计、物体重光照等。此外，我们还构建了条件化LBM框架，在可控重光照和阴影生成任务中展现出有效性。代码已开源：https://github.com/gojasper/LBM。
原文摘要 · Abstract (English)
In this paper, we introduce Latent Bridge Matching (LBM), a new, versatile and scalable method that relies on Bridge Matching in a latent space to achieve fast image-to-image translation. We show that the method can reach state-of-the-art results for various image-to-image tasks using only a single inference step. In addition to its efficiency, we also demonstrate the versatility of the method across different image translation tasks such as object removal, normal and depth estimation, and object relighting. We also derive a conditional framework of LBM and demonstrate its effectiveness by tackling the tasks of controllable image relighting and shadow generation. We provide an implementation at https://github.com/gojasper/LBM.
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