5 papers
Multi-Granularity Feature Calibration via VFM for Domain Generalized Semantic Segmentation
Xinhui Li, Xiaojie Guo
Domain Generalized Semantic Segmentation (DGSS) aims to improve the generalization ability of models across unseen domains without access to target data during training. Recent adv…
Set Pivot Learning: Redefining Generalized Segmentation with Vision Foundation Models
Xinhui Li, Xinyu He, Qiming Hu +1
In this paper, we introduce, for the first time, the concept of Set Pivot Learning, a paradigm shift that redefines domain generalization (DG) based on Vision Foundation Models (VF…
FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization
Hongze Li, Zesheng Zhou, Zhenbiao Cao +3
Traditional Federated Domain Generalization (FedDG) methods focus on learning domain-invariant features or adapting to unseen target domains, often overlooking the unique knowledge…
Differential Alignment for Domain Adaptive Object Detection
Xinyu He, Xinhui Li, Xiaojie Guo
Domain adaptive object detection (DAOD) aims to generalize an object detector trained on labeled source-domain data to a target domain without annotations, the core principle of wh…
Adaptive Texture Filtering for Single-Domain Generalized Segmentation
Xinhui Li, Mingjia Li, Yaxing Wang +2
Domain generalization in semantic segmentation aims to alleviate the performance degradation on unseen domains through learning domain-invariant features. Existing methods diversif…