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Fully Convolutional Networks for Semantic Segmentation

Fully Convolutional Networks for Semantic Segmentation

20 May 2016
Evan Shelhamer
Jonathan Long
Trevor Darrell
    VOS
    SSeg
ArXivPDFHTML

Papers citing "Fully Convolutional Networks for Semantic Segmentation"

50 / 4,298 papers shown
Title
Learning to Track at 100 FPS with Deep Regression Networks
Learning to Track at 100 FPS with Deep Regression Networks
David Held
Sebastian Thrun
Silvio Savarese
OffRL
42
1,190
0
06 Apr 2016
The Cityscapes Dataset for Semantic Urban Scene Understanding
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts
Mohamed Omran
Sebastian Ramos
Timo Rehfeld
Markus Enzweiler
Rodrigo Benenson
Uwe Franke
Stefan Roth
Bernt Schiele
202
11,493
0
06 Apr 2016
Training Constrained Deconvolutional Networks for Road Scene Semantic
  Segmentation
Training Constrained Deconvolutional Networks for Road Scene Semantic Segmentation
G. Ros
Simon Stent
P. Alcantarilla
Tomoki Watanabe
21
55
0
06 Apr 2016
Deep Image Retrieval: Learning global representations for image search
Deep Image Retrieval: Learning global representations for image search
Albert Gordo
Jon Almazán
Jérôme Revaud
Diane Larlus
23
803
0
05 Apr 2016
Good Practice in CNN Feature Transfer
Good Practice in CNN Feature Transfer
Liang Zheng
Yali Zhao
Shengjin Wang
Jingdong Wang
Q. Tian
38
160
0
01 Apr 2016
Object Skeleton Extraction in Natural Images by Fusing Scale-associated
  Deep Side Outputs
Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs
Wei Shen
Kai Zhao
Yuan Jiang
Yan Wang
Zhijiang Zhang
X. Bai
12
104
0
31 Mar 2016
Accurate Text Localization in Natural Image with Cascaded Convolutional
  Text Network
Accurate Text Localization in Natural Image with Cascaded Convolutional Text Network
Tong He
Weilin Huang
Yu Qiao
Jian Yao
32
81
0
31 Mar 2016
Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks
  with Symmetric Skip Connections
Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections
Xiao-Jiao Mao
Chunhua Shen
Yubin Yang
SupR
24
85
0
30 Mar 2016
Learning to Refine Object Segments
Learning to Refine Object Segments
Pedro H. O. Pinheiro
Nayeon Lee
R. Collobert
Piotr Dollàr
SSeg
44
854
0
29 Mar 2016
Colorful Image Colorization
Colorful Image Colorization
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
80
3,521
0
28 Mar 2016
Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation
  with Deep Gaussian CRFs
Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs
Siddhartha Chandra
Iasonas Kokkinos
27
187
0
28 Mar 2016
DeLight-Net: Decomposing Reflectance Maps into Specular Materials and
  Natural Illumination
DeLight-Net: Decomposing Reflectance Maps into Specular Materials and Natural Illumination
Stamatios Georgoulis
Konstantinos Rematas
Tobias Ritschel
Mario Fritz
Luc Van Gool
Tinne Tuytelaars
34
24
0
27 Mar 2016
Human Pose Estimation using Deep Consensus Voting
Human Pose Estimation using Deep Consensus Voting
Ita Lifshitz
Ethan Fetaya
S. Ullman
3DH
28
158
0
27 Mar 2016
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Justin Johnson
Alexandre Alahi
Li Fei-Fei
SupR
138
10,184
0
27 Mar 2016
Simple Does It: Weakly Supervised Instance and Semantic Segmentation
Simple Does It: Weakly Supervised Instance and Semantic Segmentation
Anna Khoreva
Rodrigo Benenson
J. Hosang
Matthias Hein
Bernt Schiele
WSOD
VLM
ISeg
50
742
0
24 Mar 2016
A guide to convolution arithmetic for deep learning
A guide to convolution arithmetic for deep learning
Vincent Dumoulin
Francesco Visin
FAtt
3DH
HAI
16
1,534
0
23 Mar 2016
Global-Local Face Upsampling Network
Global-Local Face Upsampling Network
Oncel Tuzel
Yuichi Taguchi
J. Hershey
CVBM
SupR
18
35
0
23 Mar 2016
Weakly-Supervised Semantic Segmentation using Motion Cues
Weakly-Supervised Semantic Segmentation using Motion Cues
P. Tokmakov
Alahari Karteek
Cordelia Schmid
27
56
0
23 Mar 2016
Semantic Object Parsing with Graph LSTM
Semantic Object Parsing with Graph LSTM
Xiaodan Liang
Xiaohui Shen
Jiashi Feng
Liang Lin
Shuicheng Yan
41
354
0
23 Mar 2016
Learning Representations for Automatic Colorization
Learning Representations for Automatic Colorization
Gustav Larsson
Michael Maire
Gregory Shakhnarovich
VLM
SSL
34
1,012
0
22 Mar 2016
Segmentation from Natural Language Expressions
Segmentation from Natural Language Expressions
Ronghang Hu
Marcus Rohrbach
Trevor Darrell
VLM
EgoV
30
426
0
20 Mar 2016
Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain
  Lesion Segmentation
Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation
Konstantinos Kamnitsas
C. Ledig
Virginia Newcombe
Joanna P. Simpson
A. D. Kane
David Menon
Daniel Rueckert
Ben Glocker
MedIm
3DV
91
3,045
0
18 Mar 2016
Generative Image Modeling using Style and Structure Adversarial Networks
Generative Image Modeling using Style and Structure Adversarial Networks
Xinyu Wang
Abhinav Gupta
GAN
39
618
0
17 Mar 2016
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural
  Networks
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
Mohammad Rastegari
Vicente Ordonez
Joseph Redmon
Ali Farhadi
MQ
90
4,333
0
16 Mar 2016
Unsupervised CNN for Single View Depth Estimation: Geometry to the
  Rescue
Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue
Ravi Garg
B. V. Kumar
G. Carneiro
Ian Reid
3DV
MDE
57
1,524
0
16 Mar 2016
Combining the Best of Convolutional Layers and Recurrent Layers: A
  Hybrid Network for Semantic Segmentation
Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation
Zhicheng Yan
Huatian Zhang
Yangqing Jia
Thomas Breuel
Yizhou Yu
SSeg
27
41
0
15 Mar 2016
Object Contour Detection with a Fully Convolutional Encoder-Decoder
  Network
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network
Jimei Yang
Brian L. Price
Scott D. Cohen
Honglak Lee
Ming-Hsuan Yang
ObjD
24
365
0
15 Mar 2016
Pushing the Limits of Deep CNNs for Pedestrian Detection
Pushing the Limits of Deep CNNs for Pedestrian Detection
Qichang Hu
Peng Wang
Chunhua Shen
Anton van den Hengel
Fatih Porikli
19
94
0
15 Mar 2016
Image Captioning with Semantic Attention
Image Captioning with Semantic Attention
Quanzeng You
Hailin Jin
Zhaowen Wang
Chen Fang
Jiebo Luo
VLM
67
1,653
0
12 Mar 2016
Optical Flow with Semantic Segmentation and Localized Layers
Optical Flow with Semantic Segmentation and Localized Layers
Laura Sevilla-Lara
Deqing Sun
Varun Jampani
Michael J. Black
24
186
0
12 Mar 2016
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
Dmitry Ulyanov
V. Lebedev
Andrea Vedaldi
Victor Lempitsky
3DH
14
944
0
10 Mar 2016
Exploring Context with Deep Structured models for Semantic Segmentation
Exploring Context with Deep Structured models for Semantic Segmentation
Guosheng Lin
Chunhua Shen
Anton van den Hengel
Ian Reid
SSeg
109
125
0
10 Mar 2016
Deep Contrast Learning for Salient Object Detection
Deep Contrast Learning for Salient Object Detection
Guanbin Li
Yizhou Yu
34
728
0
07 Mar 2016
Network Morphism
Network Morphism
Tao Wei
Changhu Wang
Y. Rui
Chen Chen
21
176
0
05 Mar 2016
Shallow and Deep Convolutional Networks for Saliency Prediction
Shallow and Deep Convolutional Networks for Saliency Prediction
Junting Pan
Kevin McGuinness
E. Sayrol
Noel E. O'Connor
Xavier Giró-i-Nieto
FAtt
38
467
0
02 Mar 2016
Weakly Supervised Localization using Deep Feature Maps
Weakly Supervised Localization using Deep Feature Maps
Archith J. Bency
H. Kwon
Hyungtae Lee
S. Karthikeyan
B. S. Manjunath
WSOL
30
73
0
01 Mar 2016
Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest
Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest
K. Sirinukunwattana
J. Pluim
Hao Chen
Xiaojuan Qi
Pheng-Ann Heng
...
Philipp Kainz
Michael Pfeiffer
M. Urschler
David R. J. Snead
Nasir M. Rajpoot
39
783
0
01 Mar 2016
Cascaded Subpatch Networks for Effective CNNs
Cascaded Subpatch Networks for Effective CNNs
Xiaoheng Jiang
Yanwei Pang
Manli Sun
Xuelong Li
39
39
0
01 Mar 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on
  Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
Sergey Ioffe
Vincent Vanhoucke
Alexander A. Alemi
191
14,161
0
23 Feb 2016
Automatic Building Extraction in Aerial Scenes Using Convolutional
  Networks
Automatic Building Extraction in Aerial Scenes Using Convolutional Networks
Jiangye Yuan
25
84
0
21 Feb 2016
A Survey of Semantic Segmentation
A Survey of Semantic Segmentation
Martin Thoma
SSeg
25
242
0
21 Feb 2016
Global Deconvolutional Networks for Semantic Segmentation
Global Deconvolutional Networks for Semantic Segmentation
Vladimir Nekrasov
Janghoon Ju
Jaesik Choi
SSeg
31
12
0
12 Feb 2016
Value Iteration Networks
Value Iteration Networks
Aviv Tamar
Yi Wu
G. Thomas
Sergey Levine
Pieter Abbeel
41
649
0
09 Feb 2016
Sub-cortical brain structure segmentation using F-CNN's
Sub-cortical brain structure segmentation using F-CNN's
Mahsa Shakeri
Stavros Tsogkas
Enzo Ferrante
S. Lippé
Samuel Kadoury
Nikos Paragios
Iasonas Kokkinos
35
119
0
05 Feb 2016
Novel Views of Objects from a Single Image
Novel Views of Objects from a Single Image
Konstantinos Rematas
Chuong H. Nguyen
Tobias Ritschel
Mario Fritz
Tinne Tuytelaars
141
73
0
31 Jan 2016
Convolutional Pose Machines
Convolutional Pose Machines
S. Wei
V. Ramakrishna
T. Kanade
Yaser Sheikh
3DV
SSL
51
2,738
0
30 Jan 2016
Hybrid CNN and Dictionary-Based Models for Scene Recognition and Domain
  Adaptation
Hybrid CNN and Dictionary-Based Models for Scene Recognition and Domain Adaptation
Guosen Xie
Xu-Yao Zhang
Shuicheng Yan
Cheng-Lin Liu
ObjD
18
149
0
29 Jan 2016
Discriminative Training of Deep Fully-connected Continuous CRF with
  Task-specific Loss
Discriminative Training of Deep Fully-connected Continuous CRF with Task-specific Loss
Fayao Liu
Guosheng Lin
Chunhua Shen
21
24
0
28 Jan 2016
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment
  using Deep Neural Networks
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks
Evan Racah
Seyoon Ko
Peter Sadowski
W. Bhimji
C. Tull
Sang-Yun Oh
Pierre Baldi
P. Prabhat
50
32
0
28 Jan 2016
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
Suraj Srinivas
Ravi Kiran Sarvadevabhatla
Konda Reddy Mopuri
N. Prabhu
S. Kruthiventi
R. Venkatesh Babu
OOD
35
216
0
25 Jan 2016
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