5 papers
Video Virtual Try-on with Conditional Diffusion Transformer Inpainter
Cheng Zou, Senlin Cheng, Bolei Xu +4
Video virtual try-on aims to naturally fit a garment to a target person in consecutive video frames. It is a challenging task, on the one hand, the output video should be in good s…
ACTIVE-o3: Empowering MLLMs with Active Perception via Pure Reinforcement Learning
Muzhi Zhu, Hao Zhong, Canyu Zhao +9
Active vision, also known as active perception, refers to actively selecting where and how to look in order to gather task-relevant information. It is a critical component of effic…
Try-On-Adapter: A Simple and Flexible Try-On Paradigm
Hanzhong Guo, Jianfeng Zhang, Cheng Zou +6
Image-based virtual try-on, widely used in online shopping, aims to generate images of a naturally dressed person conditioned on certain garments, providing significant research an…
StyleTokenizer: Defining Image Style by a Single Instance for Controlling Diffusion Models
Wen Li, Muyuan Fang, Cheng Zou +5
Despite the burst of innovative methods for controlling the diffusion process, effectively controlling image styles in text-to-image generation remains a challenging task. Many ada…
Zippo: Zipping Color and Transparency Distributions into a Single Diffusion Model
Kangyang Xie, Binbin Yang, Hao Chen +5
Beyond the superiority of the text-to-image diffusion model in generating high-quality images, recent studies have attempted to uncover its potential for adapting the learned seman…