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cs.CV2025

MagicTryOn: Harnessing Diffusion Transformer for Garment-Preserving Video Virtual Try-on

Guangyuan Li, Siming Zheng, Hao Zhang +6

Video Virtual Try-On (VVT) aims to synthesize garments that appear natural across consecutive video frames, capturing both their dynamics and interactions with human motion. Despit…

cs.CV2025

SPAST: Arbitrary Style Transfer with Style Priors via Pre-trained Large-scale Model

Zhanjie Zhang, Quanwei Zhang, Junsheng Luan +3

Given an arbitrary content and style image, arbitrary style transfer aims to render a new stylized image which preserves the content image's structure and possesses the style image…

cs.CV2025

DyArtbank: Diverse Artistic Style Transfer via Pre-trained Stable Diffusion and Dynamic Style Prompt Artbank

Zhanjie Zhang, Quanwei Zhang, Guangyuan Li +4

Artistic style transfer aims to transfer the learned style onto an arbitrary content image. However, most existing style transfer methods can only render consistent artistic styliz…

cs.CV2025

MC-VTON: Minimal Control Virtual Try-On Diffusion Transformer

Junsheng Luan, Guangyuan Li, Lei Zhao +1

Virtual try-on methods based on diffusion models achieve realistic try-on effects. They use an extra reference network or an additional image encoder to process multiple conditiona…

cs.CV2024

Rethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model

Chen Rao, Guangyuan Li, Zehua Lan +7

Current video deblurring methods have limitations in recovering high-frequency information since the regression losses are conservative with high-frequency details. Since Diffusion…

cs.CV2024

Towards Highly Realistic Artistic Style Transfer via Stable Diffusion with Step-aware and Layer-aware Prompt

Zhanjie Zhang, Quanwei Zhang, Huaizhong Lin +9

Artistic style transfer aims to transfer the learned artistic style onto an arbitrary content image, generating artistic stylized images. Existing generative adversarial network-ba…