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20182022
most citedTowards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning

7 citations · 8 across the 2 of their papers we have counts for

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9 papers · 1 filter

cs.CV20227 cited

Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning

Zaiyu Huang, Hanhui Li, Zhenyu Xie +3

In this paper, we target image-based person-to-person virtual try-on in the presence of diverse poses and large viewpoint variations. Existing methods are restricted in this settin…

cs.CV2021

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…

cs.CV20211 cited

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…

cs.CV2020

Towards Robust Partially Supervised Multi-Structure Medical Image Segmentation on Small-Scale Data

Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang +3

The data-driven nature of deep learning (DL) models for semantic segmentation requires a large number of pixel-level annotations. However, large-scale and fully labeled medical dat…

cs.CV2018

Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images

Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang +3

Convolutional neural networks have led to significant breakthroughs in the domain of medical image analysis. However, the task of breast cancer segmentation in whole-slide images (…

cs.CV2018

Query-Conditioned Three-Player Adversarial Network for Video Summarization

Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang +2

Video summarization plays an important role in video understanding by selecting key frames/shots. Traditionally, it aims to find the most representative and diverse contents in a v…