OrthoTryOn uses Orthogonal Subspace Projection on shared LoRA and Fisher-guided Negative Guidance to enable conflict-free unified fashion generation, outperforming task-specific models on benchmarks.
Fitdit: Advancing the authentic garment details for high-fidelity virtual try-on
6 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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DirectTryOn achieves state-of-the-art one-step virtual try-on performance by applying pure conditional transport, garment preservation loss, and self-consistency loss to straighten trajectories in pretrained generative models.
A new large-scale triplet dataset and diffusion transformer model using coarse human masks deliver improved video virtual try-on quality and generalization in challenging real-world conditions.
KeyTailor improves video virtual try-on realism by using instruction-guided keyframes to enhance garment details and background integrity in DiT models without major architectural changes.
FitVTON introduces a fit-aware virtual try-on model using text prompts for size control, auxiliary garment/body mask prediction, and texture rectification to achieve better sizing accuracy on diverse bodies than prior diffusion methods.
Tstars-Tryon 1.0 is a deployed virtual try-on system claiming high robustness, photorealism, multi-reference flexibility, and near real-time speed for diverse fashion items.
citing papers explorer
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OrthoTryOn: Geometric Orthogonalization for Conflict-Free Unified Fashion Generation
OrthoTryOn uses Orthogonal Subspace Projection on shared LoRA and Fisher-guided Negative Guidance to enable conflict-free unified fashion generation, outperforming task-specific models on benchmarks.
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DirectTryOn: One-Step Virtual Try-On via Straightened Conditional Transport
DirectTryOn achieves state-of-the-art one-step virtual try-on performance by applying pure conditional transport, garment preservation loss, and self-consistency loss to straighten trajectories in pretrained generative models.
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TripVVT: A Large-Scale Triplet Dataset and a Coarse-Mask Baseline for In-the-Wild Video Virtual Try-On
A new large-scale triplet dataset and diffusion transformer model using coarse human masks deliver improved video virtual try-on quality and generalization in challenging real-world conditions.
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The devil is in the details: Enhancing Video Virtual Try-On via Keyframe-Driven Details Injection
KeyTailor improves video virtual try-on realism by using instruction-guided keyframes to enhance garment details and background integrity in DiT models without major architectural changes.
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FitVTON: Fit-aware Virtual Try-On via Body-Garment Size Control
FitVTON introduces a fit-aware virtual try-on model using text prompts for size control, auxiliary garment/body mask prediction, and texture rectification to achieve better sizing accuracy on diverse bodies than prior diffusion methods.
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Tstars-Tryon 1.0: Robust and Realistic Virtual Try-On for Diverse Fashion Items
Tstars-Tryon 1.0 is a deployed virtual try-on system claiming high robustness, photorealism, multi-reference flexibility, and near real-time speed for diverse fashion items.