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Understanding image representations by measuring their equivariance and equivalence
21 November 2014
Karel Lenc
Andrea Vedaldi
SSL
FAtt
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Papers citing
"Understanding image representations by measuring their equivariance and equivalence"
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Title
Stride and Translation Invariance in CNNs
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Spectral Roll-off Points Variations: Exploring Useful Information in Feature Maps by Its Variations
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Robust Representation Learning with Feedback for Single Image Deraining
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On the Importance of Capturing a Sufficient Diversity of Perspective for the Classification of micro-PCBs
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InMoDeGAN: Interpretable Motion Decomposition Generative Adversarial Network for Video Generation
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Learning Equivariant Representations
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Learnable Gabor modulated complex-valued networks for orientation robustness
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Xianghua Xie
Elisabeth Sola
Pierre-Alain Duc
35
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23 Nov 2020
Intrinsic Image Decomposition using Paradigms
David A. Forsyth
Jason Rock
60
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20 Nov 2020
Learning Translation Invariance in CNNs
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J. Bowers
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54
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A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation
Francesco Locatello
Stefan Bauer
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Sylvain Gelly
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Olivier Bachem
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27 Oct 2020
Trajectory Prediction using Equivariant Continuous Convolution
Robin Walters
Jinxi Li
Rose Yu
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Generalizing Universal Adversarial Attacks Beyond Additive Perturbations
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Wenjie Ruan
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From Language Games to Drawing Games
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Benjamin Sattelberg
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Contextual Semantic Interpretability
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360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales
Ashesh Mishra
Chu-Song Chen
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78
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CyCNN: A Rotation Invariant CNN using Polar Mapping and Cylindrical Convolution Layers
Jinpyo Kim
Wookeun Jung
Hyungmo Kim
Jaejin Lee
56
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PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions
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A Survey on Instance Segmentation: State of the art
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On Equivariant and Invariant Learning of Object Landmark Representations
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Deep Transformation-Invariant Clustering
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Thibault Groueix
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A Hybrid Framework for Matching Printing Design Files to Product Photos
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Self-Supervised Localisation between Range Sensors and Overhead Imagery
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Shangzhe Wu
Paul Newman
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55
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Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching
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How Can CNNs Use Image Position for Segmentation?
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Group Equivariant Generative Adversarial Networks
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90
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NullSpaceNet: Nullspace Convoluional Neural Network with Differentiable Loss Function
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M. Shehata
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Feature Lenses: Plug-and-play Neural Modules for Transformation-Invariant Visual Representations
Shaohua Li
Xiuchao Sui
Jie Fu
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Rick Siow Mong Goh
39
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J. Uijlings
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35
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On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
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Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space
M. Abrishami
Amir Erfan Eshratifar
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Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
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Robin Walters
Rose Yu
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Transform-Invariant Convolutional Neural Networks for Image Classification and Search
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Translation Insensitive CNNs
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GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations
Xiang Gao
Wei Hu
Guo-Jun Qi
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RotationOut as a Regularization Method for Neural Network
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Barnabás Póczós
45
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Trung Le
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DomainSiam: Domain-Aware Siamese Network for Visual Object Tracking
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Building Deep, Equivariant Capsule Networks
Sairaam Venkatraman
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3DPC
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On the "steerability" of generative adversarial networks
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On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset
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M. Breidt
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Bernhard Schölkopf
Stefan Bauer
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On the Fairness of Disentangled Representations
Francesco Locatello
G. Abbati
Tom Rainforth
Stefan Bauer
Bernhard Schölkopf
Olivier Bachem
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Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets
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Leshem Choshen
D. Weinshall
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Disentangling Factors of Variation Using Few Labels
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Michael Tschannen
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Gunnar Rätsch
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Olivier Bachem
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103
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Making Convolutional Networks Shift-Invariant Again
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105
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Deep Comprehensive Correlation Mining for Image Clustering
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Keyu Long
Fei Wang
Chao Qian
Cheng Li
Zhouchen Lin
H. Zha
69
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0
15 Apr 2019
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