Papers Virtual Try-on
“Virtual Try-on” 태그가 달린 논문 378편 · 필터 해제
JewelTry: Mask-Free Scale Aware Jewelry Virtual Try-On
Virtual try-on (VTON) enables customers to visualize how fashion products appear when worn and has become an important technology for online shopping. While recent advances have substantially improved garment VTON, jewel…
Virtual Try-onFlowVVTON: Flow-Guided Mask-Free Video Virtual Try-On
Video virtual try-on aims to transfer a target garment onto a moving person across video frames. Current methods rely on human parsing masks or pose keypoints that frequently fail under large motions and occlusions, caus…
Virtual Try-onHuman ParsingLiveVVT: High-Fidelity Video Virtual Try-On in Real Time
Diffusion-based Video Virtual Try-On (VVT) achieves high visual fidelity through bidirectional spatio-temporal modeling, but complete-clip dependence incurs prohibitive latency and computational overhead in practical con…
Virtual Try-onInstructVVT: Instruction-Driven Video Virtual Try-On without Auxiliary Spatial Priors
Video virtual try-on is a highly constrained editing task requiring the precise replacement of a target person's clothing while strictly preserving the original video's spatial structure and temporal dynamics. Existing m…
Virtual Try-onControllable Clothing: Precise Labels and Generation for Virtual Try-On with Latent Diffusion Models
In this technical report, I present a new method for guiding image generation in the context of Virtual- Try-On (VITON). The proposed method leverages new open source Ai models to augment the image data with labels, such…
Image GenerationVirtual Try-onUniVVT: A Unified End-to-End Framework for High-Fidelity Video Virtual Try-on
Video Virtual Try-On (VVT) synthesizes a video of a person wearing a target garment while preserving identity, motion, and scene dynamics. Dominant approaches cast VVT as mask-conditioned video inpainting and rely on sep…
Video GenerationVideo InpaintingPose EstimationVirtual Try-onFashion-3DLR: A Controllable 3D Garment Generation Using Pairwise Fashion Elements for Intelligent Design
AI-generated content (AIGC) has made significant progress, with 2D generative models becoming ready-to-use tools for the digital fashion industry. However, 3D garment generation remains in its nascent stage, where in the…
Virtual Try-onOxygen-TryOn: Fashion-Native Foundation Model for Any-item Virtual Try-On
We present Oxygen-TryOn, a unified foundation model for any-item virtual try-on. Rather than repurposing a general-purpose image editor, Oxygen-TryOn is fashion-native, built for try-on through a dedicated data engine an…
Reinforcement LearningVirtual Try-onWearWow: Native 2K Multi-Garment Virtual Try-On via Adaptive Token Packing and Preference Alignment
Synthesizing native 2K multi-garment virtual try-on is a formidable frontier in digital fashion, critically bottlenecked by two fundamental limitations: the O(N^2) memory explosion induced by 2k conditions, and the spect…
Virtual Try-onTAMF-VTON: Texture-Aware Mask-Free Virtual Try-On via High-Fidelity Image Synthesis
Recent diffusion-based virtual try-on (VTON) methods remain limited by their reliance on segmentation masks, insufficient preservation of fine-grained textures, and limited support for arbitrary multi-garment composition…
Virtual Try-onHuman ParsingCtrlVTON: Controllable Virtual Try-On via Visual-Instance-Prompt Segmentation
Virtual try-on (VTO) has made significant progress in realistically transferring garments onto a target person. Yet most systems give the user little control over how a garment should be worn -- its size (loose or fitted…
Virtual Try-onImage EditingDetailAnywhere: Fashion Detail Generation via Cross-Modal Feature Alignment Distillation
Diffusion-based generative AI has achieved remarkable success in e-commerce applications such as virtual try-on, poster generation, and product background synthesis. However, when making online purchasing decisions for a…
Reinforcement LearningVirtual Try-onFDM-MFVT: Few-step Sampling Diffusion Model for Mask-Free Virtual Try-On
Image-based Virtual Try-On (IVTON) has greatly advanced through diffusion models, yet existing methods require many sampling steps and depend on masks with costly auxiliary networks. In addition, the absence of large-sca…
Virtual Try-onModaFlow: Modality-Aware Flow Matching for High-Fidelity Virtual Try-On
Image-based virtual try-on has emerged as a compelling task in e-commerce and augmented reality, yet existing methods struggle to simultaneously preserve fine garment semantics and adapt to diverse person body geometries…
Virtual Try-onOrthoTryOn: Geometric Orthogonalization for Conflict-Free Unified Fashion Generation
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…
Garment ReconstructionVirtual Try-onH-Adapter: Pose-Robust Hairstyle Transfer via Attention-Derived, Source-Aligned Hair Masks
Hairstyle transfer has practical applications such as virtual try-on, yet remains challenging when the source and reference exhibit large head-pose discrepancies. We propose H-Adapter, which improves pose robustness by t…
Text-to-Image GenerationVirtual Try-onTryOnCrafter: Unleashing Camera Trajectories for Realistic Video Virtual Try-on via a Renderable 4D Try-on Proxy
While Video Virtual Try-on (VVT) has achieved remarkable progress in synthesizing realistic garment overlays on dynamic subjects, existing paradigms remains fundamentally constrained by a passive dependency on source cam…
Virtual Try-onMakeupMirror: Improving Facial Attribute Preservation in Diffusion Models for Makeup Transfer
Makeup transfer models enable fun augmented reality (AR) experiences as well as virtual try-on (VTO) for online makeup shopping. While recent state-of-the-art diffusion based solutions such as Stable-Makeup dramatically …
Virtual Try-onFitVTON: Fit-aware Virtual Try-On via Body-Garment Size Control
While diffusion-based virtual try-on has achieved impressive visual realism, most methods treat the task as 2D inpainting, prioritizing texture preservation over physical plausibility. Consequently, they often produce pl…
Virtual Try-onHairPort: In-context 3D-aware Hair Import and Transfer for Images
Transferring hairstyles between images is an important but challenging task in computer graphics, computer vision, and visual effects. It enables users to explore new looks without physically altering their hair, with ap…
Virtual Try-on