17 citations · 19 across the 9 of their papers we have counts for
9 papers
ReImagine: Rethinking Controllable High-Quality Human Video Generation via Image-First Synthesis
Zhengwentai Sun, Keru Zheng, Chenghong Li +7
Human video generation remains challenging due to the difficulty of jointly modeling human appearance, motion, and camera viewpoint under limited multi-view data. Existing methods…
DreamVVT: Mastering Realistic Video Virtual Try-On in the Wild via a Stage-Wise Diffusion Transformer Framework
Tongchun Zuo, Zaiyu Huang, Shuliang Ning +7
Video virtual try-on (VVT) technology has garnered considerable academic interest owing to its promising applications in e-commerce advertising and entertainment. However, most exi…
Exploring Disentangled and Controllable Human Image Synthesis: From End-to-End to Stage-by-Stage
Zhengwentai Sun, Chenghong Li, Hongjie Liao +7
Achieving fine-grained controllability in human image synthesis is a long-standing challenge in computer vision. Existing methods primarily focus on either facial synthesis or near…
1-2-1: Renaissance of Single-Network Paradigm for Virtual Try-On
Shuliang Ning, Yipeng Qin, Xiaoguang Han
Virtual Try-On (VTON) has become a crucial tool in ecommerce, enabling the realistic simulation of garments on individuals while preserving their original appearance and pose. Earl…
PICTURE: PhotorealistIC virtual Try-on from UnconstRained dEsigns
Shuliang Ning, Duomin Wang, Yipeng Qin +3
In this paper, we propose a novel virtual try-on from unconstrained designs (ucVTON) task to enable photorealistic synthesis of personalized composite clothing on input human image…
MVHumanNet: A Large-scale Dataset of Multi-view Daily Dressing Human Captures
Zhangyang Xiong, Chenghong Li, Kenkun Liu +9
In this era, the success of large language models and text-to-image models can be attributed to the driving force of large-scale datasets. However, in the realm of 3D vision, while…
FashionTex: Controllable Virtual Try-on with Text and Texture
Anran Lin, Nanxuan Zhao, Shuliang Ning +3
Virtual try-on attracts increasing research attention as a promising way for enhancing the user experience for online cloth shopping. Though existing methods can generate impressiv…
MIMO Is All You Need : A Strong Multi-In-Multi-Out Baseline for Video Prediction
Shuliang Ning, Mengcheng Lan, Yanran Li +5
The mainstream of the existing approaches for video prediction builds up their models based on a Single-In-Single-Out (SISO) architecture, which takes the current frame as input to…
From Single to Multiple: Leveraging Multi-level Prediction Spaces for Video Forecasting
Mengcheng Lan, Shuliang Ning, Yanran Li +4
Despite video forecasting has been a widely explored topic in recent years, the mainstream of the existing work still limits their models with a single prediction space but complet…