activity
20222024
most citedGP-VTON: Towards General Purpose Virtual Try-on via Collaborative Local-Flow Global-Parsing Learning

9 citations · 19 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

DreamVTON: Customizing 3D Virtual Try-on with Personalized Diffusion Models

Zhenyu Xie, Haoye Dong, Yufei Gao +2

Image-based 3D Virtual Try-ON (VTON) aims to sculpt the 3D human according to person and clothes images, which is data-efficient (i.e., getting rid of expensive 3D data) but challe…

cs.CV2023

Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos

Haoyuan Li, Haoye Dong, Hanchao Jia +4

Multi-person 3D mesh recovery from videos is a critical first step towards automatic perception of group behavior in virtual reality, physical therapy and beyond. However, existing…

cs.CV2023

XFormer: Fast and Accurate Monocular 3D Body Capture

Lihui Qian, Xintong Han, Faqiang Wang +6

We present XFormer, a novel human mesh and motion capture method that achieves real-time performance on consumer CPUs given only monocular images as input. The proposed network arc…

cs.CV20239 cited

GP-VTON: Towards General Purpose Virtual Try-on via Collaborative Local-Flow Global-Parsing Learning

Zhenyu Xie, Zaiyu Huang, Xin Dong +5

Image-based Virtual Try-ON aims to transfer an in-shop garment onto a specific person. Existing methods employ a global warping module to model the anisotropic deformation for diff…

cs.CV20235 cited

Human MotionFormer: Transferring Human Motions with Vision Transformers

Hongyu Liu, Xintong Han, Chengbin Jin +8

Human motion transfer aims to transfer motions from a target dynamic person to a source static one for motion synthesis. An accurate matching between the source person and the targ…

cs.CV20225 cited

PASTA-GAN++: A Versatile Framework for High-Resolution Unpaired Virtual Try-on

Zhenyu Xie, Zaiyu Huang, Fuwei Zhao +5

Image-based virtual try-on is one of the most promising applications of human-centric image generation due to its tremendous real-world potential. In this work, we take a step forw…