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20182022
most citedAdversarial Style Mining for One-Shot Unsupervised Domain Adaptation

66 citations · 101 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CV202211 cited

Transformer Tracking with Cyclic Shifting Window Attention

Zikai Song, Junqing Yu, Yi-Ping Phoebe Chen +1

Transformer architecture has been showing its great strength in visual object tracking, for its effective attention mechanism. Existing transformer-based approaches adopt the pixel…

cs.CV202066 cited

Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation

Yawei Luo, Ping Liu, Tao Guan +2

We aim at the problem named One-Shot Unsupervised Domain Adaptation. Unlike traditional Unsupervised Domain Adaptation, it assumes that only one unlabeled target sample can be avai…

cs.CV201924 cited

Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation

Yawei Luo, Ping Liu, Tao Guan +2

For unsupervised domain adaptation problems, the strategy of aligning the two domains in latent feature space through adversarial learning has achieved much progress in image class…

cs.CV2018

Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation

Yawei Luo, Liang Zheng, Tao Guan +2

We consider the problem of unsupervised domain adaptation in semantic segmentation. The key in this campaign consists in reducing the domain shift, i.e., enforcing the data distrib…

cs.CV2018

Macro-Micro Adversarial Network for Human Parsing

Yawei Luo, Zhedong Zheng, Liang Zheng +3

In human parsing, the pixel-wise classification loss has drawbacks in its low-level local inconsistency and high-level semantic inconsistency. The introduction of the adversarial n…