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2012.04280
Cited By

Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain
Adaptation using Structurally Regularized Deep Clustering

v1v2 (latest)

Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation using Structurally Regularized Deep Clustering

8 December 2020

C. L. Philip Chen

ArXiv (abs)PDF HTML Github (9★)

Papers citing "Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation using Structurally Regularized Deep Clustering"

5 / 5 papers shown

Geometric Understanding of Discriminability and Transferability for
Visual Domain Adaptation

Geometric Understanding of Discriminability and Transferability for Visual Domain Adaptation

Chuan-Xian Ren

234

6

0

24 Jun 2024

Survey on Unsupervised Domain Adaptation for Semantic Segmentation for
Visual Perception in Automated Driving

Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated DrivingIEEE Access (IEEE Access), 2023

Manuel Schwonberg

Jan-Aike Termöhlen

Jörg P. Schäfer

Nico M. Schmidt

Hanno Gottschalk

Tim Fingscheidt

276

51

0

24 Apr 2023

Cluster-to-adapt: Few Shot Domain Adaptation for Semantic Segmentation
across Disjoint Labels

Cluster-to-adapt: Few Shot Domain Adaptation for Semantic Segmentation across Disjoint Labels

Manmohan Chandraker

254

14

0

04 Aug 2022

Generalized Label Shift Correction via Minimum Uncertainty Principle:
Theory and Algorithm

Generalized Label Shift Correction via Minimum Uncertainty Principle: Theory and Algorithm

218

3

0

26 Feb 2022

Adversarial Discriminative Domain Adaptation

Adversarial Discriminative Domain AdaptationComputer Vision and Pattern Recognition (CVPR), 2017

1.4K

5,132

0

17 Feb 2017

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