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20242026
most citedTowards Combating Frequency Simplicity-biased Learning for Domain Generalization

3 citations · 5 across the 9 of their papers we have counts for

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cs.CV2024

CA-Edit: Causality-Aware Condition Adapter for High-Fidelity Local Facial Attribute Editing

Xiaole Xian, Xilin He, Zenghao Niu +5

For efficient and high-fidelity local facial attribute editing, most existing editing methods either require additional fine-tuning for different editing effects or tend to affect…

cs.LG2024★ 3 cited

Towards Combating Frequency Simplicity-biased Learning for Domain Generalization

Xilin He, Jingyu Hu, Qinliang Lin +5

Domain generalization methods aim to learn transferable knowledge from source domains that can generalize well to unseen target domains. Recent studies show that neural networks fr…

cs.CV2024

SynFER: Towards Boosting Facial Expression Recognition with Synthetic Data

Xilin He, Cheng Luo, Xiaole Xian +8

Facial expression datasets remain limited in scale due to the subjectivity of annotations and the labor-intensive nature of data collection. This limitation poses a significant cha…

cs.CV2024

Domain-Guided Weight Modulation for Semi-Supervised Domain Generalization

Chamuditha Jayanaga Galappaththige, Zachary Izzo, Xilin He +2

Unarguably, deep learning models capable of generalizing to unseen domain data while leveraging a few labels are of great practical significance due to low developmental costs. In…

cs.CV2024★ 1 cited

Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping

Qinliang Lin, Cheng Luo, Zenghao Niu +5

Adversarial examples generated by a surrogate model typically exhibit limited transferability to unknown target systems. To address this problem, many transferability enhancement a…