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Fixing the train-test resolution discrepancy

Fixing the train-test resolution discrepancy

14 June 2019
Hugo Touvron
Andrea Vedaldi
Matthijs Douze
Hervé Jégou
ArXivPDFHTML

Papers citing "Fixing the train-test resolution discrepancy"

31 / 231 papers shown
Title
Self-supervised Neural Architecture Search
Self-supervised Neural Architecture Search
Sapir Kaplan
Raja Giryes
SSL
17
12
0
03 Jul 2020
Rethinking Channel Dimensions for Efficient Model Design
Rethinking Channel Dimensions for Efficient Model Design
Dongyoon Han
Sangdoo Yun
Byeongho Heo
Y. Yoo
3DV
6
83
0
02 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image
  Classification
Measuring Robustness to Natural Distribution Shifts in Image Classification
Rohan Taori
Achal Dave
Vaishaal Shankar
Nicholas Carlini
Benjamin Recht
Ludwig Schmidt
OOD
22
530
0
01 Jul 2020
Pyramidal Convolution: Rethinking Convolutional Neural Networks for
  Visual Recognition
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition
Ionut Cosmin Duta
Li Liu
Fan Zhu
Ling Shao
20
195
0
20 Jun 2020
Semi-Supervised Recognition under a Noisy and Fine-grained Dataset
Semi-Supervised Recognition under a Noisy and Fine-grained Dataset
Cheng Cui
Zhi-xia Ye
Yangxi Li
Xinjian Li
Min Yang
Kai Wei
B. Dai
Yanmei Zhao
Zhongji Liu
Rong Pang
11
5
0
18 Jun 2020
Unsupervised Learning of Visual Features by Contrasting Cluster
  Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCL
SSL
15
3,988
0
17 Jun 2020
Are we done with ImageNet?
Are we done with ImageNet?
Lucas Beyer
Olivier J. Hénaff
Alexander Kolesnikov
Xiaohua Zhai
Aaron van den Oord
VLM
8
395
0
12 Jun 2020
Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning
  to End
Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End
Abdelrahman Eldesokey
M. Felsberg
Karl Holmquist
M. Persson
BDL
UQCV
12
112
0
05 Jun 2020
Hide-and-Seek: A Template for Explainable AI
Hide-and-Seek: A Template for Explainable AI
Thanos Tagaris
A. Stafylopatis
6
6
0
30 Apr 2020
The Cost of Training NLP Models: A Concise Overview
The Cost of Training NLP Models: A Concise Overview
Or Sharir
Barak Peleg
Y. Shoham
15
209
0
19 Apr 2020
Time Series Data Augmentation for Neural Networks by Time Warping with a
  Discriminative Teacher
Time Series Data Augmentation for Neural Networks by Time Warping with a Discriminative Teacher
Brian Kenji Iwana
S. Uchida
AI4TS
19
86
0
19 Apr 2020
Circumventing Outliers of AutoAugment with Knowledge Distillation
Circumventing Outliers of AutoAugment with Knowledge Distillation
Longhui Wei
Anxiang Xiao
Lingxi Xie
Xin Chen
Xiaopeng Zhang
Qi Tian
8
62
0
25 Mar 2020
Meta Pseudo Labels
Meta Pseudo Labels
Hieu H. Pham
Zihang Dai
Qizhe Xie
Minh-Thang Luong
Quoc V. Le
VLM
250
656
0
23 Mar 2020
Fixing the train-test resolution discrepancy: FixEfficientNet
Fixing the train-test resolution discrepancy: FixEfficientNet
Hugo Touvron
Andrea Vedaldi
Matthijs Douze
Hervé Jégou
AAML
189
110
0
18 Mar 2020
Do CNNs Encode Data Augmentations?
Do CNNs Encode Data Augmentations?
Eddie Q. Yan
Yanping Huang
OOD
11
5
0
29 Feb 2020
MaxUp: A Simple Way to Improve Generalization of Neural Network Training
MaxUp: A Simple Way to Improve Generalization of Neural Network Training
Chengyue Gong
Tongzheng Ren
Mao Ye
Qiang Liu
AAML
6
56
0
20 Feb 2020
Big Transfer (BiT): General Visual Representation Learning
Big Transfer (BiT): General Visual Representation Learning
Alexander Kolesnikov
Lucas Beyer
Xiaohua Zhai
J. Puigcerver
Jessica Yung
Sylvain Gelly
N. Houlsby
MQ
38
1,183
0
24 Dec 2019
What it Thinks is Important is Important: Robustness Transfers through
  Input Gradients
What it Thinks is Important is Important: Robustness Transfers through Input Gradients
Alvin Chan
Yi Tay
Yew-Soon Ong
AAML
OOD
9
51
0
11 Dec 2019
Fine-grained Classification of Rowing teams
Fine-grained Classification of Rowing teams
M.J.A. van Wezel
L. J. Hamburger
Y. Napolean
24
1
0
11 Dec 2019
A Multigrid Method for Efficiently Training Video Models
A Multigrid Method for Efficiently Training Video Models
Chaoxia Wu
Ross B. Girshick
Kaiming He
Christoph Feichtenhofer
Philipp Krahenbuhl
16
94
0
02 Dec 2019
Outside the Box: Abstraction-Based Monitoring of Neural Networks
Outside the Box: Abstraction-Based Monitoring of Neural Networks
T. Henzinger
Anna Lukina
Christian Schilling
AAML
25
59
0
20 Nov 2019
Large Scale Open-Set Deep Logo Detection
Large Scale Open-Set Deep Logo Detection
M. Bastan
Hao Wu
Tianyang Cao
Bhargava Kota
Mehmet Tek
11
13
0
18 Nov 2019
Improve CAM with Auto-adapted Segmentation and Co-supervised
  Augmentation
Improve CAM with Auto-adapted Segmentation and Co-supervised Augmentation
Ziyi Kou
Guofeng Cui
Shaojie Wang
Wentian Zhao
Chenliang Xu
WSOL
9
1
0
17 Nov 2019
Self-training with Noisy Student improves ImageNet classification
Self-training with Noisy Student improves ImageNet classification
Qizhe Xie
Minh-Thang Luong
Eduard H. Hovy
Quoc V. Le
NoLa
30
2,358
0
11 Nov 2019
Progressive Compressed Records: Taking a Byte out of Deep Learning Data
Progressive Compressed Records: Taking a Byte out of Deep Learning Data
Michael Kuchnik
George Amvrosiadis
Virginia Smith
11
9
0
01 Nov 2019
Non-discriminative data or weak model? On the relative importance of
  data and model resolution
Non-discriminative data or weak model? On the relative importance of data and model resolution
Mark Sandler
Jonathan Baccash
A. Zhmoginov
Andrew G. Howard
6
31
0
07 Sep 2019
Mix & Match: training convnets with mixed image sizes for improved
  accuracy, speed and scale resiliency
Mix & Match: training convnets with mixed image sizes for improved accuracy, speed and scale resiliency
Elad Hoffer
Berry Weinstein
Itay Hubara
Tal Ben-Nun
Torsten Hoefler
Daniel Soudry
11
20
0
12 Aug 2019
Benchmarking Robustness in Object Detection: Autonomous Driving when
  Winter is Coming
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
Claudio Michaelis
Benjamin Mitzkus
Robert Geirhos
E. Rusak
Oliver Bringmann
Alexander S. Ecker
Matthias Bethge
Wieland Brendel
3DPC
19
436
0
17 Jul 2019
Implicit Pairs for Boosting Unpaired Image-to-Image Translation
Implicit Pairs for Boosting Unpaired Image-to-Image Translation
Y. Ginger
Dov Danon
Hadar Averbuch-Elor
Daniel Cohen-Or
16
2
0
15 Apr 2019
Bag of Tricks for Image Classification with Convolutional Neural
  Networks
Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He
Zhi-Li Zhang
Hang Zhang
Zhongyue Zhang
Junyuan Xie
Mu Li
219
1,399
0
04 Dec 2018
Data augmentation instead of explicit regularization
Data augmentation instead of explicit regularization
Alex Hernández-García
Peter König
30
141
0
11 Jun 2018
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