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cs.CV2025
KARST: Multi-Kernel Kronecker Adaptation with Re-Scaling Transmission for Visual Classification
Yue Zhu, Haiwen Diao, Shang Gao +2
Fine-tuning pre-trained vision models for specific tasks is a common practice in computer vision. However, this process becomes more expensive as models grow larger. Recently, para…
cs.CV2024
GSSF: Generalized Structural Sparse Function for Deep Cross-modal Metric Learning
Haiwen Diao, Ying Zhang, Shang Gao +3
Cross-modal metric learning is a prominent research topic that bridges the semantic heterogeneity between vision and language. Existing methods frequently utilize simple cosine or…
cs.CV2024
SHERL: Synthesizing High Accuracy and Efficient Memory for Resource-Limited Transfer Learning
Haiwen Diao, Bo Wan, Xu Jia +4
Parameter-efficient transfer learning (PETL) has emerged as a flourishing research field for adapting large pre-trained models to downstream tasks, greatly reducing trainable param…