40 citations · 150 across the 14 of their papers we have counts for
15 papers
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…
WarpDiffusion: Efficient Diffusion Model for High-Fidelity Virtual Try-on
xujie zhang, Xiu Li, Michael Kampffmeyer +5
Image-based Virtual Try-On (VITON) aims to transfer an in-shop garment image onto a target person. While existing methods focus on warping the garment to fit the body pose, they of…
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…
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…
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…
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…
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…
Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN
Zhenyu Xie, Zaiyu Huang, Fuwei Zhao +3
Image-based virtual try-on is one of the most promising applications of human-centric image generation due to its tremendous real-world potential. Yet, as most try-on approaches fi…
Image Comes Dancing with Collaborative Parsing-Flow Video Synthesis
Bowen Wu, Zhenyu Xie, Xiaodan Liang +3
Transferring human motion from a source to a target person poses great potential in computer vision and graphics applications. A crucial step is to manipulate sequential future mot…
M3D-VTON: A Monocular-to-3D Virtual Try-On Network
Fuwei Zhao, Zhenyu Xie, Michael Kampffmeyer +5
Virtual 3D try-on can provide an intuitive and realistic view for online shopping and has a huge potential commercial value. However, existing 3D virtual try-on methods mainly rely…
WAS-VTON: Warping Architecture Search for Virtual Try-on Network
Zhenyu Xie, Xujie Zhang, Fuwei Zhao +4
Despite recent progress on image-based virtual try-on, current methods are constraint by shared warping networks and thus fail to synthesize natural try-on results when faced with…
Fashion Editing with Adversarial Parsing Learning
Haoye Dong, Xiaodan Liang, Yixuan Zhang +6
Interactive fashion image manipulation, which enables users to edit images with sketches and color strokes, is an interesting research problem with great application value. Existin…
Towards Multi-pose Guided Virtual Try-on Network
Haoye Dong, Xiaodan Liang, Bochao Wang +3
Virtual try-on system under arbitrary human poses has huge application potential, yet raises quite a lot of challenges, e.g. self-occlusions, heavy misalignment among diverse poses…
Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis
Haoye Dong, Xiaodan Liang, Ke Gong +3
Despite remarkable advances in image synthesis research, existing works often fail in manipulating images under the context of large geometric transformations. Synthesizing person…
Deep Generative Models with Learnable Knowledge Constraints
Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov +4
The broad set of deep generative models (DGMs) has achieved remarkable advances. However, it is often difficult to incorporate rich structured domain knowledge with the end-to-end…