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Very Deep Convolutional Networks for Large-Scale Image Recognition

Very Deep Convolutional Networks for Large-Scale Image Recognition

4 September 2014
Karen Simonyan
Andrew Zisserman
    FAtt
    MDE
ArXivPDFHTML

Papers citing "Very Deep Convolutional Networks for Large-Scale Image Recognition"

50 / 10,172 papers shown
Title
When Saliency Meets Sentiment: Understanding How Image Content Invokes
  Emotion and Sentiment
When Saliency Meets Sentiment: Understanding How Image Content Invokes Emotion and Sentiment
Honglin Zheng
Tianlang Chen
Jiebo Luo
28
19
0
14 Nov 2016
How to scale distributed deep learning?
How to scale distributed deep learning?
Peter H. Jin
Qiaochu Yuan
F. Iandola
Kurt Keutzer
3DH
16
136
0
14 Nov 2016
Zero-resource Machine Translation by Multimodal Encoder-decoder Network
  with Multimedia Pivot
Zero-resource Machine Translation by Multimodal Encoder-decoder Network with Multimedia Pivot
Hideki Nakayama
Noriki Nishida
24
62
0
14 Nov 2016
Automatic discovery of discriminative parts as a quadratic assignment
  problem
Automatic discovery of discriminative parts as a quadratic assignment problem
R. Sicre
Julien Rabin
Yannis Avrithis
Teddy Furon
F. Jurie
31
6
0
14 Nov 2016
Least Squares Generative Adversarial Networks
Least Squares Generative Adversarial Networks
Xudong Mao
Qing Li
Haoran Xie
Raymond Y. K. Lau
Zhen Wang
Stephen Paul Smolley
GAN
68
4,533
0
13 Nov 2016
Leveraging Video Descriptions to Learn Video Question Answering
Leveraging Video Descriptions to Learn Video Question Answering
Kuo-Hao Zeng
Tseng-Hung Chen
Ching-Yao Chuang
Yuan-Hong Liao
Juan Carlos Niebles
Min Sun
24
175
0
12 Nov 2016
Ultimate tensorization: compressing convolutional and FC layers alike
Ultimate tensorization: compressing convolutional and FC layers alike
T. Garipov
D. Podoprikhin
Alexander Novikov
Dmitry Vetrov
37
190
0
10 Nov 2016
Deep Label Distribution Learning with Label Ambiguity
Deep Label Distribution Learning with Label Ambiguity
Bin-Bin Gao
Chao Xing
Chen-Wei Xie
Jianxin Wu
Xin Geng
25
418
0
06 Nov 2016
Boosting Image Captioning with Attributes
Boosting Image Captioning with Attributes
Ting Yao
Yingwei Pan
Yehao Li
Zhaofan Qiu
Tao Mei
VLM
31
620
0
05 Nov 2016
What Is the Best Practice for CNNs Applied to Visual Instance Retrieval?
What Is the Best Practice for CNNs Applied to Visual Instance Retrieval?
Jiedong Hao
Jing Dong
Wei Wang
T. Tan
27
10
0
05 Nov 2016
Dual Attention Networks for Multimodal Reasoning and Matching
Dual Attention Networks for Multimodal Reasoning and Matching
Hyeonseob Nam
Jung-Woo Ha
Jeonghee Kim
34
664
0
02 Nov 2016
A Benchmark Dataset and Saliency-guided Stacked Autoencoders for
  Video-based Salient Object Detection
A Benchmark Dataset and Saliency-guided Stacked Autoencoders for Video-based Salient Object Detection
Jia Li
Changqun Xia
Xiaowu Chen
18
129
0
01 Nov 2016
Visual Tracking via Boolean Map Representations
Visual Tracking via Boolean Map Representations
Kaihua Zhang
Qingshan Liu
Ming-Hsuan Yang
19
32
0
30 Oct 2016
Compact Deep Convolutional Neural Networks With Coarse Pruning
Compact Deep Convolutional Neural Networks With Coarse Pruning
S. Anwar
Wonyong Sung
3DPC
21
55
0
30 Oct 2016
Universal adversarial perturbations
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
Omar Fawzi
P. Frossard
AAML
24
2,509
0
26 Oct 2016
A Learned Representation For Artistic Style
A Learned Representation For Artistic Style
Vincent Dumoulin
Jonathon Shlens
M. Kudlur
GAN
214
1,156
0
24 Oct 2016
On Unifying Multi-View Self-Representations for Clustering by Tensor
  Multi-Rank Minimization
On Unifying Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization
Yuan Xie
Dacheng Tao
Wensheng Zhang
Lei Zhang
Yan Liu
Yanyun Qu
14
361
0
23 Oct 2016
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
180
932
0
21 Oct 2016
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of
  Convolutional Neural Networks Approaches
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches
E. Rodner
Marcel Simon
Robert B. Fisher
Joachim Denzler
17
39
0
21 Oct 2016
Exploiting inter-image similarity and ensemble of extreme learners for
  fixation prediction using deep features
Exploiting inter-image similarity and ensemble of extreme learners for fixation prediction using deep features
Hamed R. Tavakoli
Ali Borji
Jorma T. Laaksonen
Esa Rahtu
11
78
0
20 Oct 2016
Small-footprint Highway Deep Neural Networks for Speech Recognition
Small-footprint Highway Deep Neural Networks for Speech Recognition
Liang Lu
Steve Renals
30
15
0
18 Oct 2016
Big Batch SGD: Automated Inference using Adaptive Batch Sizes
Big Batch SGD: Automated Inference using Adaptive Batch Sizes
Soham De
A. Yadav
David Jacobs
Tom Goldstein
ODL
14
62
0
18 Oct 2016
Master's Thesis : Deep Learning for Visual Recognition
Master's Thesis : Deep Learning for Visual Recognition
Rémi Cadène
Nicolas Thome
Matthieu Cord
37
4
0
18 Oct 2016
Achieving Human Parity in Conversational Speech Recognition
Achieving Human Parity in Conversational Speech Recognition
Wayne Xiong
J. Droppo
Xuedong Huang
Frank Seide
M. Seltzer
A. Stolcke
Dong Yu
Geoffrey Zweig
25
576
0
17 Oct 2016
RetiNet: Automatic AMD identification in OCT volumetric data
RetiNet: Automatic AMD identification in OCT volumetric data
S. Apostolopoulos
Carlos Ciller
Sandro De Zanet
Sebastian Wolf
Raphael Sznitman
11
34
0
12 Oct 2016
Deep Learning Assessment of Tumor Proliferation in Breast Cancer
  Histological Images
Deep Learning Assessment of Tumor Proliferation in Breast Cancer Histological Images
Manan A. Shah
Christopher A. Rubadue
D. Suster
Dayong Wang
14
40
0
11 Oct 2016
Learning Low Dimensional Convolutional Neural Networks for
  High-Resolution Remote Sensing Image Retrieval
Learning Low Dimensional Convolutional Neural Networks for High-Resolution Remote Sensing Image Retrieval
Weixun Zhou
Shawn D. Newsam
Congmin Li
Z. Shao
31
183
0
10 Oct 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
18
19,541
0
07 Oct 2016
Xception: Deep Learning with Depthwise Separable Convolutions
Xception: Deep Learning with Depthwise Separable Convolutions
François Chollet
MDE
BDL
PINN
206
14,367
0
07 Oct 2016
PCA-aided Fully Convolutional Networks for Semantic Segmentation of
  Multi-channel fMRI
PCA-aided Fully Convolutional Networks for Semantic Segmentation of Multi-channel fMRI
L. Tai
Haoyang Ye
Qiong Ye
Ming-Yu Liu
22
12
0
06 Oct 2016
A Deep Spatial Contextual Long-term Recurrent Convolutional Network for
  Saliency Detection
A Deep Spatial Contextual Long-term Recurrent Convolutional Network for Saliency Detection
Nian Liu
Junwei Han
27
189
0
06 Oct 2016
Exploiting Depth from Single Monocular Images for Object Detection and
  Semantic Segmentation
Exploiting Depth from Single Monocular Images for Object Detection and Semantic Segmentation
Yuanzhouhan Cao
Chunhua Shen
Heng Tao Shen
MDE
26
65
0
06 Oct 2016
DeepGaze II: Reading fixations from deep features trained on object
  recognition
DeepGaze II: Reading fixations from deep features trained on object recognition
Matthias Kümmerer
Thomas S. A. Wallis
Matthias Bethge
16
287
0
05 Oct 2016
Tutorial on Answering Questions about Images with Deep Learning
Tutorial on Answering Questions about Images with Deep Learning
Mateusz Malinowski
Mario Fritz
VLM
24
3
0
04 Oct 2016
Prediction of Manipulation Actions
Prediction of Manipulation Actions
Cornelia Fermuller
Fang Wang
Yezhou Yang
Konstantinos Zampogiannis
Yi Zhang
Francisco Barranco
Michael Pfeiffer
16
51
0
03 Oct 2016
One-Trial Correction of Legacy AI Systems and Stochastic Separation
  Theorems
One-Trial Correction of Legacy AI Systems and Stochastic Separation Theorems
Alexander N. Gorban
I. Romanenko
Richard Burton
I. Tyukin
19
29
0
03 Oct 2016
Accelerating Deep Convolutional Networks using low-precision and
  sparsity
Accelerating Deep Convolutional Networks using low-precision and sparsity
Ganesh Venkatesh
Eriko Nurvitadhi
Debbie Marr
26
135
0
02 Oct 2016
Very Deep Convolutional Neural Networks for Robust Speech Recognition
Very Deep Convolutional Neural Networks for Robust Speech Recognition
Y. Qian
P. Woodland
11
81
0
02 Oct 2016
How Transferable are CNN-based Features for Age and Gender
  Classification?
How Transferable are CNN-based Features for Age and Gender Classification?
Gökhan Özbulak
Y. Aytar
H. K. Ekenel
CVBM
19
105
0
01 Oct 2016
Very Deep Convolutional Neural Networks for Raw Waveforms
Very Deep Convolutional Neural Networks for Raw Waveforms
Wei Dai
Chia Dai
Shuhui Qu
Juncheng Billy Li
Samarjit Das
15
343
0
01 Oct 2016
A deep representation for depth images from synthetic data
A deep representation for depth images from synthetic data
Fabio Maria Carlucci
P. Russo
Barbara Caputo
MDE
3DV
4
34
0
30 Sep 2016
Caffeinated FPGAs: FPGA Framework For Convolutional Neural Networks
Caffeinated FPGAs: FPGA Framework For Convolutional Neural Networks
R. Dicecco
Griffin Lacey
Jasmina Vasiljevic
P. Chow
Graham W. Taylor
S. Areibi
19
92
0
30 Sep 2016
Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the
  Amazon Picking Challenge
Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge
Andy Zeng
Kuan-Ting Yu
Shuran Song
Daniel Suo
Ed Walker
Alberto Rodriguez
Jianxiong Xiao
SSL
6
458
0
29 Sep 2016
Classifier comparison using precision
Classifier comparison using precision
Lovedeep Gondara
9
3
0
29 Sep 2016
CNN Architectures for Large-Scale Audio Classification
CNN Architectures for Large-Scale Audio Classification
Shawn Hershey
Sourish Chaudhuri
D. Ellis
J. Gemmeke
A. Jansen
...
Rif A. Saurous
Bryan Seybold
M. Slaney
Ron J. Weiss
K. Wilson
31
2,468
0
29 Sep 2016
Variational Autoencoder for Deep Learning of Images, Labels and Captions
Variational Autoencoder for Deep Learning of Images, Labels and Captions
Yunchen Pu
Zhe Gan
Ricardo Henao
Xin Yuan
Chunyuan Li
Andrew Stevens
Lawrence Carin
BDL
CoGe
19
745
0
28 Sep 2016
Understanding data augmentation for classification: when to warp?
Understanding data augmentation for classification: when to warp?
S. Wong
Adam Gatt
V. Stamatescu
Mark D Mcdonnell
13
898
0
28 Sep 2016
Learning Language-Visual Embedding for Movie Understanding with
  Natural-Language
Learning Language-Visual Embedding for Movie Understanding with Natural-Language
Atousa Torabi
Niket Tandon
Leonid Sigal
14
97
0
26 Sep 2016
Optimistic and Pessimistic Neural Networks for Scene and Object
  Recognition
Optimistic and Pessimistic Neural Networks for Scene and Object Recognition
René Grzeszick
Sebastian Sudholt
G. Fink
UQCV
36
4
0
26 Sep 2016
Input Convex Neural Networks
Input Convex Neural Networks
Brandon Amos
Lei Xu
J. Zico Kolter
178
598
0
22 Sep 2016
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