Fashion image editing demands high-dimensional, fine-grained control to follow personalized, unpredictable natural-language instructions. Yet current methods are limited by a fundamental trade-off: fashion-specific approaches offer structural accuracy but lack semantic flexibility, while general text-driven editors are...
Yuran Dong, Bo Du, Mang Ye· IEEE Transactions on Pattern...· 0 citations
Federated Graph Learning (FGL) enables privacy-preserving GNN training over distributed graph data, yet dynamic task streams in Federated Graph Continual Learning (FGCL) inevitably lead to catastrophic forgetting. From a spectral perspective, this forgetting manifests as two fundamental challenges: high-frequency incon...
Hanyao Guo, Zihan Tan, Wen-Ke Huang et al.· Proceedings of the 32nd ACM...· 0 citations
Federated Graph Learning (FGL) enables privacy-preserving GNN training over distributed graph data, yet dynamic task streams in Federated Graph Continual Learning (FGCL) inevitably lead to catastrophic forgetting. From a spectral perspective, this forgetting manifests as two fundamental challenges: high-frequency incon...
Hanyao Guo, Zihan Tan, Wenke Huang et al.· Proceedings of the 32nd ACM...· 0 citations
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