1 citations · 1 across the 5 of their papers we have counts for
7 papers
AnyCrowd: Instance-Isolated Identity-Pose Binding for Arbitrary Multi-Character Animation
Zhenyu Xie, Ji Xia, Michael Kampffmeyer +9
Controllable character animation has advanced rapidly in recent years, yet multi-character animation remains underexplored. As the number of characters grows, multi-character refer…
FastFit: Accelerating Multi-Reference Virtual Try-On via Cacheable Diffusion Models
Zheng Chong, Yanwei Lei, Shiyue Zhang +7
Despite its great potential, virtual try-on technology is hindered from real-world application by two major challenges: the inability of current methods to support multi-reference…
ComposeAnyone: Controllable Layout-to-Human Generation with Decoupled Multimodal Conditions
Shiyue Zhang, Zheng Chong, Xi Lu +6
Building on the success of diffusion models, significant advancements have been made in multimodal image generation tasks. Among these, human image generation has emerged as a prom…
CatV2TON: Taming Diffusion Transformers for Vision-Based Virtual Try-On with Temporal Concatenation
Zheng Chong, Wenqing Zhang, Shiyue Zhang +6
Virtual try-on (VTON) technology has gained attention due to its potential to transform online retail by enabling realistic clothing visualization of images and videos. However, mo…
GarmentAligner: Text-to-Garment Generation via Retrieval-augmented Multi-level Corrections
Shiyue Zhang, Zheng Chong, Xujie Zhang +4
General text-to-image models bring revolutionary innovation to the fields of arts, design, and media. However, when applied to garment generation, even the state-of-the-art text-to…
CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models
Zheng Chong, Xiao Dong, Haoxiang Li +6
Virtual try-on methods based on diffusion models achieve realistic effects but often require additional encoding modules, a large number of training parameters, and complex preproc…