Making Convolutional Networks Shift-Invariant Again

25 April 2019

Papers citing "Making Convolutional Networks Shift-Invariant Again"

25 / 175 papers shown

Title
Knee Injury Detection using MRI with Efficiently-Layered Network (ELNet) Chen-Han Tsai N. Kiryati Eli Konen I. Eshed Arnaldo Mayer MedIm 11 34 0 06 May 2020
RANSAC-Flow: generic two-stage image alignment Xi Shen Franccois Darmon Alexei A. Efros Mathieu Aubry 27 87 0 03 Apr 2020
TResNet: High Performance GPU-Dedicated Architecture T. Ridnik Hussam Lawen Asaf Noy Emanuel Ben-Baruch Gilad Sharir Itamar Friedman OOD 31 211 0 30 Mar 2020
Leveraging Frequency Analysis for Deep Fake Image Recognition Joel Frank Thorsten Eisenhofer Lea Schonherr Asja Fischer D. Kolossa Thorsten Holz 16 530 0 19 Mar 2020
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation Huiyu Wang Yukun Zhu Bradley Green Hartwig Adam Alan Yuille Liang-Chieh Chen 3DPC 28 658 0 17 Mar 2020
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location O. Kayhan Jan van Gemert 211 233 0 16 Mar 2020
Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance Matthew Gadd D. Martini Paul Newman 24 48 0 10 Mar 2020
Volumetric landmark detection with a multi-scale shift equivariant neural network Tianyu Ma Ajay Gupta M. Sabuncu 3DPC 37 17 0 03 Mar 2020
Do CNNs Encode Data Augmentations? Eddie Q. Yan Yanping Huang OOD 18 5 0 29 Feb 2020
Attention! A Lightweight 2D Hand Pose Estimation Approach Nicholas Santavas Ioannis Kansizoglou Loukas Bampis E. Karakasis Antonios Gasteratos 17 50 0 22 Jan 2020
Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network Jungkyu Lee Taeryun Won Tae Kwan Lee Hyemin Lee Geonmo Gu K. Hong 34 57 0 17 Jan 2020
A simple way to make neural networks robust against diverse image corruptions E. Rusak Lukas Schott Roland S. Zimmermann Julian Bitterwolf Oliver Bringmann Matthias Bethge Wieland Brendel 21 64 0 16 Jan 2020
Total Deep Variation for Linear Inverse Problems Erich Kobler Alexander Effland K. Kunisch Thomas Pock 17 89 0 14 Jan 2020
CNN-generated images are surprisingly easy to spot... for now Sheng-Yu Wang Oliver Wang Richard Y. Zhang Andrew Owens Alexei A. Efros OOD 54 944 0 23 Dec 2019
Self-training with Noisy Student improves ImageNet classification Qizhe Xie Minh-Thang Luong Eduard H. Hovy Quoc V. Le NoLa 88 2,364 0 11 Nov 2019
A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks Takanori Maehara Hoang NT 27 29 0 09 Oct 2019
DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm System Ankur Handa Karl Van Wyk Wei Yang Jacky Liang Yu-Wei Chao Qian Wan Stan Birchfield Nathan D. Ratliff Dieter Fox 30 197 0 07 Oct 2019
Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation Hang Gao Xizhou Zhu Steve Lin Jifeng Dai 21 64 0 07 Oct 2019
PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices Xiaolong Ma Fu-Ming Guo Wei Niu Xue Lin Jian Tang Kaisheng Ma Bin Ren Yanzhi Wang CVBM 27 173 0 06 Sep 2019
LIP: Local Importance-based Pooling Ziteng Gao Limin Wang Gangshan Wu FAtt 37 94 0 12 Aug 2019
Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields Evan Shelhamer Dequan Wang Trevor Darrell 29 35 0 25 Apr 2019
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 306 10,378 0 12 Dec 2018
Strike (with) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects Michael A. Alcorn Melvin Johnson Zhitao Gong Chengfei Wang Long Mai Naveen Ari Stella Laurenzo 47 299 0 28 Nov 2018
Why do deep convolutional networks generalize so poorly to small image transformations? Aharon Azulay Yair Weiss 37 556 0 30 May 2018
Learning SO(3) Equivariant Representations with Spherical CNNs Carlos Esteves Christine Allen-Blanchette A. Makadia Kostas Daniilidis 65 510 0 17 Nov 2017