Learning to Sample the Most Useful Training Patches from Images

Learning to Sample the Most Useful Training Patches from Images

24 November 2020

Shuyang Sun

Philip H. S. Torr

Papers citing "Learning to Sample the Most Useful Training Patches from Images"

4 / 4 papers shown

Title
SamplingAug: On the Importance of Patch Sampling Augmentation for Single Image Super-Resolution Shizun Wang Ming Lu Kaixin Chen Jiaming Liu Xiaoqi Li Chuang Zhang Ming Wu 11 6 0 30 Nov 2021
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank Inigo Alonso Alberto Sabater David Ferstl Luis Montesano Ana C. Murillo SSL CLL 119 202 0 27 Apr 2021
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 268 10,214 0 16 Nov 2016
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi Jose Caballero Ferenc Huszár J. Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang SupR 190 5,163 0 16 Sep 2016