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20182021
most citedAdversarial Style Mining for One-Shot Unsupervised Domain Adaptation

66 citations · 94 across the 4 of their papers we have counts for

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8 papers · 1 filter

cs.CV20212 cited

Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes

Jian-Wei Zhang, Lei Lv, Yawei Luo +3

Few-shot segmentation~(FSS) performance has been extensively promoted by introducing episodic training and class-wise prototypes. However, the FSS problem remains challenging due t…

cs.CV20212 cited

VidFace: A Full-Transformer Solver for Video FaceHallucination with Unaligned Tiny Snapshots

Yuan Gan, Yawei Luo, Xin Yu +2

In this paper, we investigate the task of hallucinating an authentic high-resolution (HR) human face from multiple low-resolution (LR) video snapshots. We propose a pure transforme…

cs.CV2021

Improving Weakly-supervised Object Localization via Causal Intervention

Feifei Shao, Yawei Luo, Li Zhang +4

The recent emerged weakly supervised object localization (WSOL) methods can learn to localize an object in the image only using image-level labels. Previous works endeavor to perce…

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.CV2020

Copy and Paste GAN: Face Hallucination from Shaded Thumbnails

Yang Zhang, Ivor Tsang, Yawei Luo +3

Existing face hallucination methods based on convolutional neural networks (CNN) have achieved impressive performance on low-resolution (LR) faces in a normal illumination conditio…

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…