2 citations · 3 across the 6 of their papers we have counts for
7 papers
FIT: A Large-Scale Dataset for Fit-Aware Virtual Try-On
Johanna Karras, Yuanhao Wang, Yingwei Li +1
Given a person and a garment image, virtual try-on (VTO) aims to synthesize a realistic image of the person wearing the garment, while preserving their original pose and identity.…
Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps
Sandeep Mishra, Yasamin Jafarian, Andreas Lugmayr +5
Photographs of people taken by professional photographers typically present the person in beautiful lighting, with an interesting pose, and flattering quality. This is unlike commo…
HoloGarment: 360° Novel View Synthesis of In-the-Wild Garments
Johanna Karras, Yingwei Li, Yasamin Jafarian +1
Novel view synthesis (NVS) of in-the-wild garments is a challenging task due significant occlusions, complex human poses, and cloth deformations. Prior methods rely on synthetic 3D…
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…
Continual Adversarial Defense
Qian Wang, Hefei Ling, Yingwei Li +3
In response to the rapidly evolving nature of adversarial attacks against visual classifiers, numerous defenses have been proposed to generalize against as many known attacks as po…
Harnessing Perceptual Adversarial Patches for Crowd Counting
Shunchang Liu, Jiakai Wang, Aishan Liu +4
Crowd counting, which has been widely adopted for estimating the number of people in safety-critical scenes, is shown to be vulnerable to adversarial examples in the physical world…