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FCSS: Fully Convolutional Self-Similarity for Dense Semantic
  Correspondence

FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence

3 February 2017
Seungryong Kim
Dongbo Min
Bumsub Ham
Sangryul Jeon
Stephen Lin
Kwanghoon Sohn
ArXivPDFHTML

Papers citing "FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence"

22 / 22 papers shown
Title
MATCHA:Towards Matching Anything
Fei Xue
Sven Elflein
Laura Leal-Taixe
Qunjie Zhou
79
0
0
28 Jan 2025
Robust Image Matching By Dynamic Feature Selection
Robust Image Matching By Dynamic Feature Selection
Hao Huang
Jianchun Chen
Xiang Li
Lingjing Wang
Yi Fang
84
3
0
13 Aug 2020
Universal Correspondence Network
Universal Correspondence Network
Chris Choy
JunYoung Gwak
Silvio Savarese
Manmohan Chandraker
39
368
0
11 Jun 2016
Fully Convolutional Networks for Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer
Jonathan Long
Trevor Darrell
VOS
SSeg
251
37,704
0
20 May 2016
Learning Dense Correspondence via 3D-guided Cycle Consistency
Learning Dense Correspondence via 3D-guided Cycle Consistency
Tinghui Zhou
Philipp Krahenbuhl
Mathieu Aubry
Qi-Xing Huang
Alexei A. Efros
108
385
0
18 Apr 2016
LIFT: Learned Invariant Feature Transform
LIFT: Learned Invariant Feature Transform
K. M. Yi
Eduard Trulls
Vincent Lepetit
Pascal Fua
90
1,203
0
30 Mar 2016
Deep Metric Learning via Lifted Structured Feature Embedding
Deep Metric Learning via Lifted Structured Feature Embedding
Hyun Oh Song
Yu Xiang
Stefanie Jegelka
Silvio Savarese
FedML
SSL
DML
48
1,641
0
19 Nov 2015
Proposal Flow
Proposal Flow
Bumsub Ham
Minsu Cho
Cordelia Schmid
Jean Ponce
32
140
0
16 Nov 2015
Stereo Matching by Training a Convolutional Neural Network to Compare
  Image Patches
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches
Jure Zbontar
Yann LeCun
3DV
123
1,384
0
20 Oct 2015
Spatial Transformer Networks
Spatial Transformer Networks
Max Jaderberg
Karen Simonyan
Andrew Zisserman
Koray Kavukcuoglu
249
7,361
0
05 Jun 2015
Dense Semantic Correspondence where Every Pixel is a Classifier
Dense Semantic Correspondence where Every Pixel is a Classifier
H. Bristow
Jack Valmadre
Simon Lucey
25
56
0
15 May 2015
Learning to Compare Image Patches via Convolutional Neural Networks
Learning to Compare Image Patches via Convolutional Neural Networks
Sergey Zagoruyko
N. Komodakis
SSL
54
1,434
0
14 Apr 2015
Domain-Size Pooling in Local Descriptors: DSP-SIFT
Domain-Size Pooling in Local Descriptors: DSP-SIFT
Jingming Dong
Stefano Soatto
36
190
0
30 Dec 2014
Hypercolumns for Object Segmentation and Fine-grained Localization
Hypercolumns for Object Segmentation and Fine-grained Localization
Bharath Hariharan
Pablo Arbeláez
Ross B. Girshick
Jitendra Malik
SSeg
92
1,594
0
21 Nov 2014
Do Convnets Learn Correspondence?
Do Convnets Learn Correspondence?
Jonathan Long
Ning Zhang
Trevor Darrell
52
312
0
04 Nov 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
746
99,991
0
04 Sep 2014
Discriminative Unsupervised Feature Learning with Exemplar Convolutional
  Neural Networks
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks
Alexey Dosovitskiy
Philipp Fischer
Jost Tobias Springenberg
Martin Riedmiller
Thomas Brox
OOD
SSL
49
1,018
0
26 Jun 2014
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual
  Recognition
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
ObjD
221
11,183
0
18 Jun 2014
Detect What You Can: Detecting and Representing Objects using Holistic
  Models and Body Parts
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts
Xianjie Chen
Roozbeh Mottaghi
Xiaobai Liu
Sanja Fidler
R. Urtasun
Alan Yuille
48
639
0
08 Jun 2014
Descriptor Matching with Convolutional Neural Networks: a Comparison to SIFT
Philipp Fischer
Alexey Dosovitskiy
Thomas Brox
46
276
0
22 May 2014
Multi-scale Orderless Pooling of Deep Convolutional Activation Features
Multi-scale Orderless Pooling of Deep Convolutional Activation Features
Yunchao Gong
Liwei Wang
Ruiqi Guo
Svetlana Lazebnik
144
1,090
0
07 Mar 2014
DeCAF: A Deep Convolutional Activation Feature for Generic Visual
  Recognition
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Jeff Donahue
Yangqing Jia
Oriol Vinyals
Judy Hoffman
Ning Zhang
Eric Tzeng
Trevor Darrell
VLM
ObjD
128
4,946
0
06 Oct 2013
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