8 papers
DirectTryOn: One-Step Virtual Try-On via Straightened Conditional Transport
Xianbing Sun, Jiahui Zhan, Liqing Zhang +1
Recent diffusion- and flow-based VTON methods achieve strong results with pretrained generative models, but their reliance on multi-step sampling incurs high inference cost, while…
Masked Generative Transformer Is What You Need for Image Editing
Wei Chow, Linfeng Li, Xian Sun +14
Diffusion models dominate image editing, yet their global denoising mechanism entangles edited regions with surrounding context, causing modifications to propagate into areas that…
Is Your Driving World Model an All-Around Player?
Lingdong Kong, Ao Liang, Tianyi Yan +20
Today's driving world models can generate remarkably realistic dash-cam videos, yet no single model excels universally. Some generate photorealistic textures but violate basic phys…
AVGGT: Rethinking Global Attention for Accelerating VGGT
Xianbing Sun, Zhikai Zhu, Zhengyu Lou +5
Models such as VGGT and have shown strong multi-view 3D performance, but their heavy reliance on global self-attention results in high computational cost. Existing sparse-at…
Towards Source-Aware Object Swapping with Initial Noise Perturbation
Jiahui Zhan, Xianbing Sun, Xiangnan Zhu +4
Object swapping aims to replace a source object in a scene with a reference object while preserving object fidelity, scene fidelity, and object-scene harmony. Existing methods eith…
VTONGuard: Automatic Detection and Authentication of AI-Generated Virtual Try-On Content
Shengyi Wu, Yan Hong, Shengyao Chen +5
With the rapid advancement of generative AI, virtual try-on (VTON) systems are becoming increasingly common in e-commerce and digital entertainment. However, the growing realism of…