no code implementations • 20 Mar 2024 • Jeffrey Zhang, Kedan Li, Shao-Yu Chang, David Forsyth
Virtual Try-on (VTON) involves generating images of a person wearing selected garments.
no code implementations • 4 Jan 2024 • Jeffrey Zhang, Shao-Yu Chang, Kedan Li, David Forsyth
The usual practice of training the denoiser with a very noisy image and starting inference with a sample of pure noise leads to inconsistent generated images during inference.
no code implementations • 29 Nov 2022 • Kedan Li, Jeffrey Zhang, Shao-Yu Chang, David Forsyth
However, no current method can both control how the garment is worn -- including tuck or untuck, opened or closed, high or low on the waist, etc.. -- and generate realistic images that accurately preserve the properties of the original garment.
no code implementations • CVPR 2021 • Kedan Li, Min Jin Chong, Jeffrey Zhang, Jingen Liu
Prior works produce images that are filled with artifacts and fail to capture important visual details necessary for commercial applications.
no code implementations • 22 Mar 2020 • Kedan Li, Min Jin Chong, Jingen Liu, David Forsyth
However, obtaining a realistic image is challenging because the kinematics of garments is complex and because outline, texture, and shading cues in the image reveal errors to human viewers.
no code implementations • 17 Jun 2019 • Kedan Li, Chen Liu, David Forsyth
A user study suggests that people understand the match between the queries and the outfits produced by our method.