3 citations · 5 across the 4 of their papers we have counts for
4 papers
Semi-supervised Semantic Segmentation via Boosting Uncertainty on Unlabeled Data
Daoan Zhang, Yunhao Luo, Jianguo Zhang
We bring a new perspective to semi-supervised semantic segmentation by providing an analysis on the labeled and unlabeled distributions in training datasets. We first figure out th…
Cross Contrasting Feature Perturbation for Domain Generalization
Chenming Li, Daoan Zhang, Wenjian Huang +1
Domain generalization (DG) aims to learn a robust model from source domains that generalize well on unseen target domains. Recent studies focus on generating novel domain samples o…
Bootstrap The Original Latent: Learning a Private Model from a Black-box Model
Shuai Wang, Daoan Zhang, Jianguo Zhang +2
In this paper, considering the balance of data/model privacy of model owners and user needs, we propose a new setting called Back-Propagated Black-Box Adaptation (BPBA) for users t…
Feature Alignment and Uniformity for Test Time Adaptation
Shuai Wang, Daoan Zhang, Zipei Yan +2
Test time adaptation (TTA) aims to adapt deep neural networks when receiving out of distribution test domain samples. In this setting, the model can only access online unlabeled te…