T-SVDNet: Exploring High-Order Prototypical Correlations for
Multi-Source Domain Adaptation

T-SVDNet: Exploring High-Order Prototypical Correlations for Multi-Source Domain Adaptation

30 July 2021

Papers citing "T-SVDNet: Exploring High-Order Prototypical Correlations for Multi-Source Domain Adaptation"

10 / 10 papers shown

Title
Adaptive Hardness-driven Augmentation and Alignment Strategies for Multi-Source Domain Adaptations Yang Yuxiang Zeng Xinyi Zeng Pinxian Zu Chen Yan Binyu Zhou Jiliu Wang Yan 43 0 0 02 Jan 2025
Learning with Alignments: Tackling the Inter- and Intra-domain Shifts for Cross-multidomain Facial Expression Recognition Yuxiang Yang L. Wen Xinyi Zeng Yuanyuan Xu Xi Wu Jiliu Zhou Yan Wang 34 3 0 08 Jul 2024
Enhancing Domain Adaptation through Prompt Gradient Alignment Hoang Phan Lam C. Tran Quyen Tran Trung Le 52 0 0 13 Jun 2024
Domain-Agnostic Mutual Prompting for Unsupervised Domain Adaptation Zhekai Du Xinyao Li Fengling Li Ke Lu Lei Zhu Jingjing Li 43 16 0 05 Mar 2024
CNG-SFDA: Clean-and-Noisy Region Guided Online-Offline Source-Free Domain Adaptation Hyeonwoo Cho Chanmin Park Donghee Kim Jinyoung Kim Won Hwa Kim TTA 31 0 0 26 Jan 2024
Subspace Identification for Multi-Source Domain Adaptation Zijian Li Ruichu Cai Guan-Hong Chen Boyang Sun Zhifeng Hao Kun Zhang 36 33 0 07 Oct 2023
Partial Identifiability for Domain Adaptation Lingjing Kong Shaoan Xie Weiran Yao Yujia Zheng Guan-Hong Chen P. Stojanov Victor Akinwande Kun Zhang 53 9 0 10 Jun 2023
DynaMask: Dynamic Mask Selection for Instance Segmentation Ruihuang Li Chenhang He Shuai Li Yabin Zhang Lei Zhang ISeg 32 16 0 14 Mar 2023
Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm Canyi Lu Jiashi Feng Yudong Chen Wei Liu Zhouchen Lin Shuicheng Yan 56 737 0 10 Apr 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015