11 citations · 19 across the 7 of their papers we have counts for
7 papers
Source-Free Domain Adaptation with Vision-Language Prior
Song Tang, Yunxiang Bai, Wenxin Su +3
Source-Free Domain Adaptation (SFDA) seeks to adapt a source model, which is pre-trained on a supervised source domain, for a target domain, with only access to unlabeled target tr…
Consistent text-to-image generation via scene de-contextualization
Song Tang, Peihao Gong, Kunyu Li +5
Consistent text-to-image (T2I) generation seeks to produce identity-preserving images of the same subject across diverse scenes, yet it often fails due to a phenomenon called ident…
Few-Shot Medical Image Segmentation with High-Fidelity Prototypes
Song Tang, Shaxu Yan, Xiaozhi Qi +4
Few-shot Semantic Segmentation (FSS) aims to adapt a pretrained model to new classes with as few as a single labelled training sample per class. Despite the prototype based approac…
Proxy Denoising for Source-Free Domain Adaptation
Song Tang, Wenxin Su, Yan Gan +3
Source-Free Domain Adaptation (SFDA) aims to adapt a pre-trained source model to an unlabeled target domain with no access to the source data. Inspired by the success of large Visi…
Unified Source-Free Domain Adaptation
Song Tang, Wenxin Su, Mao Ye +2
In the pursuit of transferring a source model to a target domain without access to the source training data, Source-Free Domain Adaptation (SFDA) has been extensively explored acro…
Learning Semantic-Agnostic and Spatial-Aware Representation for Generalizable Visual-Audio Navigation
Hongcheng Wang, Yuxuan Wang, Fangwei Zhong +4
Visual-audio navigation (VAN) is attracting more and more attention from the robotic community due to its broad applications, \emph{e.g.}, household robots and rescue robots. In th…
Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation
Song Tang, Yan Yang, Zhiyuan Ma +5
In the classic setting of unsupervised domain adaptation (UDA), the labeled source data are available in the training phase. However, in many real-world scenarios, owing to some re…