arXiv AI
ShoeFit: A New Dataset and Dual-image-stream DiT Framework for Virtual Footwear Try-On
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TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioning
arXiv:2609.39335v1 Announce Type: new Abstract: Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce. However, existing met...
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Structure-Detail Decoupled Autoregressive Generation for Fast and High-Fidelity Virtual Try-On
arXiv:2607.11233v2 Announce Type: replace Abstract: Virtual try-on (VTON) is a bi-conditional image generation problem that requires not only accurate person preservation but also faithful garment de...
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Spatio-Temporal Garment Reconstruction Using Diffusion Mapping via Pattern Coordinates
arXiv:2602.24043v2 Announce Type: replace Abstract: Reconstructing 3D clothed humans from monocular images and videos is a fundamental problem with applications in virtual try-on, avatar creation, an...
arXiv Computer Vision
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OmniFabric: Coherent UV Space Texture Synthesis for 3D Garment Reconstruction
OmniFabric is a new method for creating production‑ready 3D garment assets from a single image. It generates globally coherent texture maps directly in the 2D sewing pattern (UV) space, using a coarse initialization from Vision‑Language Models and refining it with a diffusion transformer conditioned on 3D positional features. The approach removes distortion and baked‑in artifacts, producing photorealistic 3D garments with high‑quality textures that outperform current state‑of‑the‑art baselines.
arXiv AI
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NI-Tex: Non-isometric Image-based Garment Texture Generation
arXiv:2511. 18765v3 Announce Type: replace-cross Abstract: Existing industrial 3D garment meshes already cover most real-world clothing geometries, yet their texture diversity remains limited.
Hugging Face Trending Papers
Sep 24
OmniFabric: Coherent UV Space Texture Synthesis for 3D Garment Reconstruction
OmniFabric is a new method for creating high‑quality, globally coherent texture maps for 3D garment reconstruction from a single image. It first generates a coarse texture initialization on the garment’s sewing pattern using a 3D mesh and Vision‑Language Model priors, then refines this in the UV domain with a diffusion transformer conditioned on 3D positional features. The approach removes distortion and baked‑in artifacts, producing photorealistic 3D garments that outperform existing baselines.