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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 / 13,190 papers shown
Title
UberNet: Training a `Universal' Convolutional Neural Network for Low-,
  Mid-, and High-Level Vision using Diverse Datasets and Limited Memory
UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory
Iasonas Kokkinos
SSeg
SSL
50
670
0
07 Sep 2016
Visual Saliency Detection Based on Multiscale Deep CNN Features
Visual Saliency Detection Based on Multiscale Deep CNN Features
Guanbin Li
Yizhou Yu
FAtt
44
337
0
07 Sep 2016
Human pose estimation via Convolutional Part Heatmap Regression
Human pose estimation via Convolutional Part Heatmap Regression
Adrian Bulat
Georgios Tzimiropoulos
3DH
33
517
0
06 Sep 2016
Best-Buddies Similarity - Robust Template Matching using Mutual Nearest
  Neighbors
Best-Buddies Similarity - Robust Template Matching using Mutual Nearest Neighbors
Shaul Oron
Tali Dekel
Tianfan Xue
William T. Freeman
S. Avidan
3DV
16
80
0
06 Sep 2016
Deep Retinal Image Understanding
Deep Retinal Image Understanding
Kevis-Kokitsi Maninis
Jordi Pont-Tuset
Pablo Arbeláez
Luc Van Gool
33
507
0
05 Sep 2016
A Deep Multi-Level Network for Saliency Prediction
A Deep Multi-Level Network for Saliency Prediction
Marcella Cornia
Lorenzo Baraldi
G. Serra
Rita Cucchiara
FAtt
31
345
0
05 Sep 2016
Deep Learning Human Mind for Automated Visual Classification
Deep Learning Human Mind for Automated Visual Classification
C. Spampinato
S. Palazzo
I. Kavasidis
Daniela Giordano
M. Shah
Nasim Souly
36
224
0
01 Sep 2016
Grid Loss: Detecting Occluded Faces
Grid Loss: Detecting Occluded Faces
M. Opitz
Georg Waltner
Georg Poier
Horst Possegger
Horst Bischof
CVBM
41
76
0
01 Sep 2016
Robustness of classifiers: from adversarial to random noise
Robustness of classifiers: from adversarial to random noise
Alhussein Fawzi
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
16
367
0
31 Aug 2016
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
93
3,660
0
31 Aug 2016
What makes ImageNet good for transfer learning?
What makes ImageNet good for transfer learning?
Minyoung Huh
Pulkit Agrawal
Alexei A. Efros
OOD
SSeg
VLM
SSL
62
671
0
30 Aug 2016
Multi-Class Multi-Object Tracking using Changing Point Detection
Multi-Class Multi-Object Tracking using Changing Point Detection
Byungjae Lee
Enkhbayar Erdenee
SongGuo Jin
P. Rhee
VOT
16
25
0
30 Aug 2016
Visual Question: Predicting If a Crowd Will Agree on the Answer
Visual Question: Predicting If a Crowd Will Agree on the Answer
Danna Gurari
Kristen Grauman
HAI
29
2
0
29 Aug 2016
Linking Image and Text with 2-Way Nets
Linking Image and Text with 2-Way Nets
Aviv Eisenschtat
Lior Wolf
27
176
0
29 Aug 2016
Approaching the Computational Color Constancy as a Classification
  Problem through Deep Learning
Approaching the Computational Color Constancy as a Classification Problem through Deep Learning
Seoung Wug Oh
Seon Joo Kim
3DV
23
100
0
29 Aug 2016
3D Object Proposals using Stereo Imagery for Accurate Object Class
  Detection
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection
Xiaozhi Chen
Kaustav Kundu
Yukun Zhu
Huimin Ma
Sanja Fidler
R. Urtasun
3DPC
44
365
0
27 Aug 2016
Scalable Compression of Deep Neural Networks
Scalable Compression of Deep Neural Networks
Xing Wang
Jie Liang
21
4
0
26 Aug 2016
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking
Hyeonseob Nam
Mooyeol Baek
Bohyung Han
VOT
30
329
0
25 Aug 2016
Title Generation for User Generated Videos
Title Generation for User Generated Videos
Kuo-Hao Zeng
Tseng-Hung Chen
Juan Carlos Niebles
Min Sun
35
69
0
25 Aug 2016
A 4D Light-Field Dataset and CNN Architectures for Material Recognition
A 4D Light-Field Dataset and CNN Architectures for Material Recognition
Tingxian Wang
Jun-Yan Zhu
Hiroaki Ebi
Manmohan Chandraker
Alexei A. Efros
R. Ramamoorthi
3DV
21
185
0
24 Aug 2016
Searching Action Proposals via Spatial Actionness Estimation and
  Temporal Path Inference and Tracking
Searching Action Proposals via Spatial Actionness Estimation and Temporal Path Inference and Tracking
Nannan Li
Dan Xu
Zhenqiang Ying
Zhihao Li
Ge Li
11
13
0
23 Aug 2016
CrowdNet: A Deep Convolutional Network for Dense Crowd Counting
CrowdNet: A Deep Convolutional Network for Dense Crowd Counting
Lokesh Boominathan
S. Kruthiventi
R. Venkatesh Babu
16
550
0
22 Aug 2016
Local Binary Convolutional Neural Networks
Local Binary Convolutional Neural Networks
Felix Juefei Xu
Vishnu Boddeti
Marios Savvides
MQ
32
251
0
22 Aug 2016
Lets keep it simple, Using simple architectures to outperform deeper and
  more complex architectures
Lets keep it simple, Using simple architectures to outperform deeper and more complex architectures
S. H. HasanPour
Mohammad Rouhani
Mohsen Fayyaz
Mohammad Sabokrou
23
119
0
22 Aug 2016
phi-LSTM: A Phrase-based Hierarchical LSTM Model for Image Captioning
phi-LSTM: A Phrase-based Hierarchical LSTM Model for Image Captioning
Y. Tan
Chee Seng Chan
VLM
22
29
0
20 Aug 2016
A Recurrent Encoder-Decoder Network for Sequential Face Alignment
A Recurrent Encoder-Decoder Network for Sequential Face Alignment
Xi Peng
Rogerio Feris
Xiaoyu Wang
Dimitris N. Metaxas
CVBM
180
140
0
19 Aug 2016
Photo Filter Recommendation by Category-Aware Aesthetic Learning
Photo Filter Recommendation by Category-Aware Aesthetic Learning
Wei-Tse Sun
T. Chao
Y. Kuo
Winston H. Hsu
30
44
0
18 Aug 2016
Seeing with Humans: Gaze-Assisted Neural Image Captioning
Seeing with Humans: Gaze-Assisted Neural Image Captioning
Yusuke Sugano
Andreas Bulling
24
68
0
18 Aug 2016
Saliency Detection via Combining Region-Level and Pixel-Level
  Predictions with CNNs
Saliency Detection via Combining Region-Level and Pixel-Level Predictions with CNNs
Youbao Tang
Xiangqian Wu
28
74
0
18 Aug 2016
Deeply-Supervised Recurrent Convolutional Neural Network for Saliency
  Detection
Deeply-Supervised Recurrent Convolutional Neural Network for Saliency Detection
Youbao Tang
Xiangqian Wu
Wei Bu
16
48
0
18 Aug 2016
Multi-stage Object Detection with Group Recursive Learning
Multi-stage Object Detection with Group Recursive Learning
Jianan Li
Xiaodan Liang
Jianshu Li
Tingfa Xu
Jiashi Feng
Shuicheng Yan
ObjD
24
50
0
18 Aug 2016
IM2CAD
IM2CAD
Hamid Izadinia
Qi Shan
S. M. Seitz
3DV
21
192
0
18 Aug 2016
Depth2Action: Exploring Embedded Depth for Large-Scale Action
  Recognition
Depth2Action: Exploring Embedded Depth for Large-Scale Action Recognition
Yi Zhu
Shawn D. Newsam
27
41
0
15 Aug 2016
Design of Efficient Convolutional Layers using Single Intra-channel
  Convolution, Topological Subdivisioning and Spatial "Bottleneck" Structure
Design of Efficient Convolutional Layers using Single Intra-channel Convolution, Topological Subdivisioning and Spatial "Bottleneck" Structure
Min Wang
Baoyuan Liu
H. Foroosh
27
51
0
15 Aug 2016
Generating Synthetic Data for Text Recognition
Generating Synthetic Data for Text Recognition
Praveen Krishnan
C. V. Jawahar
25
55
0
15 Aug 2016
Stacked Approximated Regression Machine: A Simple Deep Learning Approach
Stacked Approximated Regression Machine: A Simple Deep Learning Approach
Zhangyang Wang
Shiyu Chang
Qing Ling
Shuai Huang
Xia Hu
Honghui Shi
Thomas S. Huang
BDL
15
2
0
14 Aug 2016
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image
  Denoising
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Peng Sun
W. Zuo
Yunjin Chen
Deyu Meng
Lei Zhang
SupR
77
6,931
0
13 Aug 2016
Beyond Correlation Filters: Learning Continuous Convolution Operators
  for Visual Tracking
Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking
Martin Danelljan
Andreas Robinson
Fahad Shahbaz Khan
Michael Felsberg
21
1,692
0
12 Aug 2016
Learning Structured Sparsity in Deep Neural Networks
Learning Structured Sparsity in Deep Neural Networks
W. Wen
Chunpeng Wu
Yandan Wang
Yiran Chen
Hai Helen Li
47
2,323
0
12 Aug 2016
Clockwork Convnets for Video Semantic Segmentation
Clockwork Convnets for Video Semantic Segmentation
Evan Shelhamer
Kate Rakelly
Judy Hoffman
Trevor Darrell
37
199
0
11 Aug 2016
Solving Visual Madlibs with Multiple Cues
Solving Visual Madlibs with Multiple Cues
Tatiana Tommasi
Arun Mallya
Bryan A. Plummer
Svetlana Lazebnik
Alexander C. Berg
Tamara L. Berg
37
18
0
11 Aug 2016
Fashion Landmark Detection in the Wild
Fashion Landmark Detection in the Wild
Ziwei Liu
Sijie Yan
Ping Luo
Xiaogang Wang
Xiaoou Tang
24
171
0
10 Aug 2016
Mining Fashion Outfit Composition Using An End-to-End Deep Learning
  Approach on Set Data
Mining Fashion Outfit Composition Using An End-to-End Deep Learning Approach on Set Data
Y. Li
Liangliang Cao
Jiang Zhu
Jiebo Luo
27
188
0
10 Aug 2016
Residual Networks of Residual Networks: Multilevel Residual Networks
Residual Networks of Residual Networks: Multilevel Residual Networks
Ke Zhang
Miao Sun
T. Han
Xingfang Yuan
Liru Guo
Tao Liu
26
303
0
09 Aug 2016
Convolutional Oriented Boundaries
Convolutional Oriented Boundaries
Kevis-Kokitsi Maninis
Jordi Pont-Tuset
Pablo Arbelaez
Luc Van Gool
13
231
0
09 Aug 2016
Mean Box Pooling: A Rich Image Representation and Output Embedding for
  the Visual Madlibs Task
Mean Box Pooling: A Rich Image Representation and Output Embedding for the Visual Madlibs Task
Ashkan Mokarian
Mateusz Malinowski
Mario Fritz
27
5
0
09 Aug 2016
Discriminatively Trained Latent Ordinal Model for Video Classification
Discriminatively Trained Latent Ordinal Model for Video Classification
Karan Sikka
Gaurav Sharma
24
11
0
08 Aug 2016
Adapting Deep Network Features to Capture Psychological Representations
Adapting Deep Network Features to Capture Psychological Representations
Joshua C. Peterson
Joshua T. Abbott
Thomas Griffiths
6
66
0
06 Aug 2016
Play and Learn: Using Video Games to Train Computer Vision Models
Play and Learn: Using Video Games to Train Computer Vision Models
Alireza Shafaei
James J. Little
Mark Schmidt
36
109
0
05 Aug 2016
Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos
Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos
Suman Saha
Gurkirt Singh
Michael Sapienza
Philip Torr
Fabio Cuzzolin
ViT
39
206
0
04 Aug 2016
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