22 citations · 29 across the 6 of their papers we have counts for
6 papers
Fashion-VDM: Video Diffusion Model for Virtual Try-On
Johanna Karras, Yingwei Li, Nan Liu +5
We present Fashion-VDM, a video diffusion model (VDM) for generating virtual try-on videos. Given an input garment image and person video, our method aims to generate a high-qualit…
M&M VTO: Multi-Garment Virtual Try-On and Editing
Luyang Zhu, Yingwei Li, Nan Liu +3
We present M&M VTO, a mix and match virtual try-on method that takes as input multiple garment images, text description for garment layout and an image of a person. An example inpu…
TryOnDiffusion: A Tale of Two UNets
Luyang Zhu, Dawei Yang, Tyler Zhu +5
Given two images depicting a person and a garment worn by another person, our goal is to generate a visualization of how the garment might look on the input person. A key challenge…
RGB-D Local Implicit Function for Depth Completion of Transparent Objects
Luyang Zhu, Arsalan Mousavian, Yu Xiang +4
Majority of the perception methods in robotics require depth information provided by RGB-D cameras. However, standard 3D sensors fail to capture depth of transparent objects due to…
Reconstructing NBA Players
Luyang Zhu, Konstantinos Rematas, Brian Curless +2
Great progress has been made in 3D body pose and shape estimation from a single photo. Yet, state-of-the-art results still suffer from errors due to challenging body poses, modelin…
Learning to Estimate 3D Human Pose and Shape from a Single Color Image
Georgios Pavlakos, Luyang Zhu, Xiaowei Zhou +1
This work addresses the problem of estimating the full body 3D human pose and shape from a single color image. This is a task where iterative optimization-based solutions have typi…