Category Contrast for Unsupervised Domain Adaptation in Visual Tasks-Reference-Cited by-同舟云学术

Category Contrast for Unsupervised Domain Adaptation in Visual Tasks

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
Short-container-title:

Author:

Huang Jiaxing¹,Guan Dayan¹,Xiao Aoran¹,Lu Shijian¹,Shao Ling²

Affiliation:

1. Nanyang Technological University,Singapore

2. Terminus Group,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09878909.pdf?arnumber=9878909

Reference81 articles.

1. Un-supervised embedding learning via invariant and spreading instance feature;mang;Proceedings of the IEEE/CVF Confer-ence on Computer Vision and Pattern Recognition,0

2. FDA: Fourier Domain Adaptation for Semantic Segmentation

3. Exploring categorical regularization for domain adap-tive object detection;xu;Proceedings of the IEEE/CVF Con-ference on Computer Vision and Pattern Recognition,0

4. Multi-Level Domain Adaptive Learning for Cross-Domain Detection

5. Prototypical pseudo label denoising and target structure learning for domain adaptive semantic segmen-tation;zhang;Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,0

Cited by 91 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deformation depth decoupling network for point cloud domain adaptation;Neural Networks;2024-12

2. Cross-domain aspect-based sentiment classification with hybrid prompt;Expert Systems with Applications;2024-12

3. Unsupervised domain adaptation with hard-sample dividing and processing strategy;Information Sciences;2024-10

4. Unsupervised domain adaptive segmentation algorithm based on two-level category alignment;Neural Networks;2024-09

5. A global reweighting approach for cross-domain semantic segmentation;Signal Processing: Image Communication;2024-09