3 papers
cs.LG2026
Group-Shared Low-Rank Approximation for Mobile-Efficient Pointwise Convolutions in Large-Kernel CNNs
Hao Luo, Yiting Yang, Wenyi Zhao +10
Large-kernel Convolutional Neural Networks (CNNs) deliver remarkable performance in vision tasks by significantly expanding receptive fields, yet their quadratic parameter growth c…
cs.CV2025
Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy
Yiting Yang, Hao Luo, Yuan Sun +7
A prevalent approach in Parameter-Efficient Fine-Tuning (PEFT) of pre-trained Vision Transformers (ViT) involves freezing the majority of the backbone parameters and solely learnin…
cs.CV2024
Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
Wei Dong, Yuan Sun, Yiting Yang +7
A common strategy for Parameter-Efficient Fine-Tuning (PEFT) of pre-trained Vision Transformers (ViTs) involves adapting the model to downstream tasks by learning a low-rank adapta…