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20232025
most citedLearning with Alignments: Tackling the Inter- and Intra-domain Shifts for Cross-multidomain Facial Expression Recognition

1 citations · 2 across the 8 of their papers we have counts for

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cs.CV2025

BASIC: Semi-supervised Multi-organ Segmentation with Balanced Subclass Regularization and Semantic-conflict Penalty

Zhenghao Feng, Lu Wen, Yuanyuan Xu +4

Semi-supervised learning (SSL) has shown notable potential in relieving the heavy demand of dense prediction tasks on large-scale well-annotated datasets, especially for the challe…

cs.CV2024★ 1 cited

Learning with Alignments: Tackling the Inter- and Intra-domain Shifts for Cross-multidomain Facial Expression Recognition

Yuxiang Yang, Lu Wen, Xinyi Zeng +4

Facial Expression Recognition (FER) holds significant importance in human-computer interactions. Existing cross-domain FER methods often transfer knowledge solely from a single lab…

cs.CV2024

Adaptive Prompt Learning with Negative Textual Semantics and Uncertainty Modeling for Universal Multi-Source Domain Adaptation

Yuxiang Yang, Lu Wen, Yuanyuan Xu +2

Universal Multi-source Domain Adaptation (UniMDA) transfers knowledge from multiple labeled source domains to an unlabeled target domain under domain shifts (different data distrib…

cs.CV2024

Dose Prediction Driven Radiotherapy Paramters Regression via Intra- and Inter-Relation Modeling

Jiaqi Cui, Yuanyuan Xu, Jianghong Xiao +4

Deep learning has facilitated the automation of radiotherapy by predicting accurate dose distribution maps. However, existing methods fail to derive the desirable radiotherapy para…

cs.CV2023★ 1 cited

Diffusion-based Radiotherapy Dose Prediction Guided by Inter-slice Aware Structure Encoding

Zhenghao Feng, Lu Wen, Jianghong Xiao +5

Deep learning (DL) has successfully automated dose distribution prediction in radiotherapy planning, enhancing both efficiency and quality. However, existing methods suffer from th…