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GarVerseLOD is a high‑fidelity 3D garment reconstruction dataset created by The Chinese University of Hong Kong (Shenzhen). It contains 6,000 garment models handcrafted by professional artists with fine geometric details. The dataset offers three Levels of Detail (LOD): a coarse shape with no detail, a stylized shape with pose‑blended detail, and a pixel‑aligned detail level. During creation, a conditional diffusion model generated a large number of high‑quality paired images to enhance dataset generalization. GarVerseLOD is primarily intended for single‑image in‑the‑wild 3D garment reconstruction, addressing the limitations of existing methods in handling complex garment deformations and diverse poses.
