Abstract
Synthetic data provide low-cost, accurately annotated samples for geometry-sensitive vision tasks, but appearance and imaging differences between synthetic and real domains cause severe domain shift and degrade downstream performance. Unpaired synthetic-to-real translation can reduce this gap without paired supervision, yet existing methods often face a trade-off between photorealism and structural stability: unconstrained generation may introduce deformation or spurious textures, while overly rigid constraints limit adaptation to real-domain statistics. We propose FD-DB, a frequency-decoupled dual-branch model that separates appearance transfer into low-frequency interpretable editing and high-frequency residual compensation. The interpretable branch predicts physically meaningful editing parameters (white balance, exposure, contrast, saturation, blur, and grain) to build a stable low-frequency appearance base with strong content preservation. The free branch complements fine details through residual generation, and a gated fusion mechanism combines the two branches under explicit frequency constraints to limit low-frequency drift. We further adopt a two-stage training schedule that first stabilizes the editing branch and then releases the residual branch to improve optimization stability. Experiments on the YCB-V dataset show that FD-DB improves real-domain appearance consistency and significantly boosts downstream semantic segmentation performance while preserving geometric and semantic structures.
Abstract (translated)
合成数据为几何敏感的视觉任务提供了低成本且准确标注的数据样本，但合成与真实场景之间的外观和成像差异导致了严重的领域偏移，并降低了下游任务的表现。无配对的合成到真实的转换可以减少这种差距而无需配对监督，然而现有方法常常在照片逼真度和结构稳定性之间做出权衡：不受约束的生成可能会引入形变或虚假纹理，而过于严格的限制又会限制向真实领域统计信息的适应能力。 我们提出了一种名为FD-DB（频率解耦双分支模型）的方法。该模型将外观转换分解为低频可解释编辑和高频残差补偿两个部分。可解释分支预测物理上合理的编辑参数（白平衡、曝光度、对比度、饱和度、模糊度和颗粒感），从而构建一个稳定的低频外观基础，同时保持强烈的内容保真性。自由分支则通过残差生成来补充细节信息，并且采用门控融合机制在明确的频率约束下将两个分支结合起来以限制低频漂移。 我们进一步采用了两阶段训练计划，先稳定编辑分支，再释放残差分支，从而提升优化稳定性。在YCB-V数据集上的实验表明，FD-DB显著提高了真实领域的外观一致性，并且在保持几何和语义结构的同时，大幅提升了下游的语义分割性能。
URL
https://arxiv.org/abs/2602.09476
