Pretraining Image Encoders without Reconstruction via Feature Prediction Loss

16 March 2020

Papers citing "Pretraining Image Encoders without Reconstruction via Feature Prediction Loss"

8 / 8 papers shown

Title
AutoAugment: Learning Augmentation Policies from Data E. D. Cubuk Barret Zoph Dandelion Mané Vijay Vasudevan Quoc V. Le 118 1,771 0 24 May 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Y. Zhang Phillip Isola Alexei A. Efros Eli Shechtman Oliver Wang EGVM 327 11,734 0 11 Jan 2018
Beyond the Pixel-Wise Loss for Topology-Aware Delineation Agata Mosinska Pablo Márquez-Neila Mateusz Koziñski Pascal Fua 3DV 63 231 0 06 Dec 2017
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 204 5,073 0 05 Jun 2016
Perceptual Losses for Real-Time Style Transfer and Super-Resolution Justin Johnson Alexandre Alahi Li Fei-Fei SupR 218 10,230 0 27 Mar 2016
One weird trick for parallelizing convolutional neural networks A. Krizhevsky GNN 88 1,298 0 23 Apr 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 243 14,893 1 21 Dec 2013
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 289 7,279 0 20 Dec 2013