核心概念
Deep features often lack spatial resolution for dense prediction tasks, but FeatUp restores lost spatial information without altering semantics.
統計資料
FeatUp solves critical problems in computer vision by enhancing deep features' spatial resolution.
ResNet-50 produces 7x7 deep features from a 224x224 pixel input (32x resolution reduction).
FeaTup outperforms other feature upsampling approaches in class activation map generation, transfer learning for segmentation and depth prediction, and end-to-end training for semantic segmentation.
引述
"Deep models learn high-quality features but at prohibitively low spatial resolutions." - Content
"FeatUp significantly outperforms other feature upsampling approaches in various downstream tasks." - Content