OrthoTryOn: Geometric Orthogonalization for Conflict-Free Unified Fashion Generation

• URL: http://arxiv.org/abs/2606.27880v1
• Date: Fri, 26 Jun 2026 09:23:25 GMT
• Title: OrthoTryOn: Geometric Orthogonalization for Conflict-Free Unified Fashion Generation
• Abstract summary: Unified fashion generation integrates tasks like virtual try-on and garment reconstruction into a single model to reduce task-specific adaptation costs.<n>We propose OrthoTryOn, a unified framework mitigating this interference within a shared Low- AdaptationRank (LoRA) module.
• Score: 43.40052085990979
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Unified fashion generation integrates tasks like virtual try-on and garment reconstruction into a single model to reduce task-specific adaptation costs. However, naive parameter sharing across semantically distinct tasks induces negative transfer through severe inter-task gradient conflict. We propose OrthoTryOn, a unified framework mitigating this interference within a shared Low-Rank Adaptation (LoRA) module. Its Orthogonal Subspace Projection (OSP) applies task-specific orthogonal rotations to bottleneck features, mapping them into decorrelated coordinate frames. To address residual semantic coupling at inference time, we further propose Fisher-guided Negative Guidance (FNG), a parameter-free strategy that utilizes diagonal Fisher information to quantify inter-task sensitivity overlap and explicitly repels generation trajectories from the most confusable task via Classifier-Free Guidance. Extensive experiments demonstrate that OrthoTryOn avoids the severe performance degradation typical of naive unified training and even surpasses independently trained task-specific models, achieving state-of-the-art results across multiple benchmarks while generalizing robustly across diverse diffusion backbones. Code is available at https://github.com/NJU-PCALab/OrthoTryOn.

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