atlas

Research map / Architectures and efficiency / CNN design

Deep Global Generalized Gaussian Networks

CVPR 2019 · Architectures and efficiency › CNN design · approach: Compact CNN architectures · 18 citations (OpenAlex)

Check your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace Gaussian covariance pooling with generalized-Gaussian covariance poolingResNet-50 · ImageNet-1Ktop-1 error: 21.95 -> 21.31Helped
Replace Gaussian covariance pooling with generalized-Gaussian covariance poolingResNet-50 · Places365top-1 error: 43.68 -> 43.07Helped
Add robust covariance estimation (ablation)3G-Net with ResNet-50 · ImageNet-1Ktop-1 error: 25.17 -> 21.31Helped
Add robust covariance estimation (ablation)3G-Net with ResNet-101 · ImageNet-1Ktop-1 error: 24.23 -> 20.37Helped
Use three re-weighting iterations instead of one (ablation)3G-Net with ResNet-50 · ImageNet-1Ktop-1 error: 21.64 -> 21.31Helped
Replace the full re-weighted block with URM-v1 (ablation)3G-Net with ResNet-50 · ImageNet-1Ktop-1 error: 21.31 -> 21.97Hurt
Replace the full re-weighted block with URM-v2 (ablation)3G-Net with ResNet-50 · ImageNet-1Ktop-1 error: 21.31 -> 21.89Hurt
Add the element-wise power operation to the re-weighted block (ablation)3G-Net · ImageNet-1Kclassification performanceNo clear effect

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy