Probability-Flow Distillation exactly matches the Wasserstein gradient flow of the target distribution when distilling 2D diffusion priors into 3D models, yielding higher-fidelity results than SDS or SDI.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
SIFT-VTON adds explicit geometric supervision from SIFT keypoints to diffusion-based virtual try-on to improve spatial alignment and detail preservation.
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Probability-Flow Distillation: Exact Wasserstein Gradient Flow for High-Fidelity 3D Generation
Probability-Flow Distillation exactly matches the Wasserstein gradient flow of the target distribution when distilling 2D diffusion priors into 3D models, yielding higher-fidelity results than SDS or SDI.
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SIFT-VTON: Geometric Correspondence Supervision on Cross-Attention for Virtual Try-On
SIFT-VTON adds explicit geometric supervision from SIFT keypoints to diffusion-based virtual try-on to improve spatial alignment and detail preservation.