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cs.CV2026
LoCA: Spatially-Aware Low-Rank Convolutional Adaptation of Vision Foundation Models
Sojung An, Junha Lee, Sujeong You +2
Pre-trained Vision Foundation Models (VFMs) provide strong visual representations for diverse downstream tasks. The key challenge of VFM adaptation stems from the prohibitive costs…
cs.CV2025
Dataset Distillation for Super-Resolution without Class Labels and Pre-trained Models
Sunwoo Cho, Yejin Jung, Nam Ik Cho +1
Training deep neural networks has become increasingly demanding, requiring large datasets and significant computational resources, especially as model complexity advances. Data dis…
cs.CV2025
Efficient Attention-Sharing Information Distillation Transformer for Lightweight Single Image Super-Resolution
Karam Park, Jae Woong Soh, Nam Ik Cho
Transformer-based Super-Resolution (SR) methods have demonstrated superior performance compared to convolutional neural network (CNN)-based SR approaches due to their capability to…