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Shuaicheng Niu

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.LG1
ORCID 0000-0001-8212-1831
same name
  • Shuaicheng Niu — 17 papers, h 16
  • Shuaicheng Niu — 7 papers, h 6
  • Shuaicheng Niu — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedTowards Stable Test-Time Adaptation in Dynamic Wild World

63 citations · 70 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 4 cited

Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction

Zeshuai Deng, Zhuokun Chen, Shuaicheng Niu +3

Image super-resolution (SR) aims to learn a mapping from low-resolution (LR) to high-resolution (HR) using paired HR-LR training images. Conventional SR methods typically gather th…

cs.CV2023

Imbalance-Agnostic Source-Free Domain Adaptation via Avatar Prototype Alignment

Hongbin Lin, Mingkui Tan, Yifan Zhang +5

Source-free Unsupervised Domain Adaptation (SF-UDA) aims to adapt a well-trained source model to an unlabeled target domain without access to the source data. One key challenge is…

cs.LG2023★ 63 cited

Towards Stable Test-Time Adaptation in Dynamic Wild World

Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang +4

Test-time adaptation (TTA) has shown to be effective at tackling distribution shifts between training and testing data by adapting a given model on test samples. However, the onlin…

cs.CV2022★ 3 cited

Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation

Hongbin Lin, Yifan Zhang, Zhen Qiu +4

This paper studies a new, practical but challenging problem, called Class-Incremental Unsupervised Domain Adaptation (CI-UDA), where the labeled source domain contains all classes,…

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