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ImageNet Large Scale Visual Recognition Challenge
v1v2v3 (latest)

ImageNet Large Scale Visual Recognition Challenge

1 September 2014
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
Sean Ma
Zhiheng Huang
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
    VLMObjD
ArXiv (abs)PDFHTML

Papers citing "ImageNet Large Scale Visual Recognition Challenge"

50 / 11,094 papers shown
Title
PN-Net: Conjoined Triple Deep Network for Learning Local Image
  Descriptors
PN-Net: Conjoined Triple Deep Network for Learning Local Image Descriptors
Vassileios Balntas
Edward Johns
Lilian Tang
K. Mikolajczyk
95
173
0
19 Jan 2016
Scale-aware Pixel-wise Object Proposal Networks
Scale-aware Pixel-wise Object Proposal Networks
Zequn Jie
Xiaodan Liang
Jiashi Feng
W. Lu
Francis E. H. Tay
Shuicheng Yan
ObjD
89
30
0
19 Jan 2016
Combining Markov Random Fields and Convolutional Neural Networks for
  Image Synthesis
Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis
Chuan Li
Michael Wand
117
771
0
18 Jan 2016
Multimodal Pivots for Image Caption Translation
Multimodal Pivots for Image Caption Translation
Julian Hitschler
Shigehiko Schamoni
Stefan Riezler
167
97
0
15 Jan 2016
Deep Neural Networks predict Hierarchical Spatio-temporal Cortical
  Dynamics of Human Visual Object Recognition
Deep Neural Networks predict Hierarchical Spatio-temporal Cortical Dynamics of Human Visual Object Recognition
Radoslaw Martin Cichy
A. Khosla
D. Pantazis
Antonio Torralba
A. Oliva
3DH
68
70
0
12 Jan 2016
Using Filter Banks in Convolutional Neural Networks for Texture
  Classification
Using Filter Banks in Convolutional Neural Networks for Texture Classification
Vincent Andrearczyk
P. Whelan
3DV
135
252
0
12 Jan 2016
Exploiting Local Structures with the Kronecker Layer in Convolutional
  Networks
Exploiting Local Structures with the Kronecker Layer in Convolutional Networks
Shuchang Zhou
Jia-Nan Wu
Yuxin Wu
Xinyu Zhou
88
41
0
31 Dec 2015
The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses
The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses
Jiaqian Yu
Matthew Blaschko
89
38
0
24 Dec 2015
Adaptive Object Detection Using Adjacency and Zoom Prediction
Adaptive Object Detection Using Adjacency and Zoom Prediction
Y. Lu
T. Javidi
Svetlana Lazebnik
ObjD
104
76
0
24 Dec 2015
Recent Advances in Convolutional Neural Networks
Recent Advances in Convolutional Neural Networks
Jiuxiang Gu
Zhenhua Wang
Jason Kuen
Lianyang Ma
Amir Shahroudy
...
Xingxing Wang
Li Wang
Gang Wang
Jianfei Cai
Tsuhan Chen
365
5,269
0
22 Dec 2015
Deep Learning with S-shaped Rectified Linear Activation Units
Deep Learning with S-shaped Rectified Linear Activation Units
Xiaojie Jin
Chunyan Xu
Jiashi Feng
Yunchao Wei
Junjun Xiong
Shuicheng Yan
432
219
0
22 Dec 2015
Seeing through the Human Reporting Bias: Visual Classifiers from Noisy
  Human-Centric Labels
Seeing through the Human Reporting Bias: Visual Classifiers from Noisy Human-Centric Labels
Ishan Misra
C. L. Zitnick
Margaret Mitchell
Ross B. Girshick
NoLa
97
219
0
22 Dec 2015
Quantized Convolutional Neural Networks for Mobile Devices
Quantized Convolutional Neural Networks for Mobile Devices
Jiaxiang Wu
Cong Leng
Yuhang Wang
Qinghao Hu
Jian Cheng
MQ
201
1,171
0
21 Dec 2015
Poseidon: A System Architecture for Efficient GPU-based Deep Learning on
  Multiple Machines
Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines
Huatian Zhang
Zhiting Hu
Jinliang Wei
P. Xie
Gunhee Kim
Qirong Ho
Eric Xing
GNN
63
48
0
19 Dec 2015
Blockout: Dynamic Model Selection for Hierarchical Deep Networks
Blockout: Dynamic Model Selection for Hierarchical Deep Networks
Calvin Murdock
Zerui Li
Howard Zhou
Tom Duerig
OODBDL
88
47
0
16 Dec 2015
We Are Humor Beings: Understanding and Predicting Visual Humor
We Are Humor Beings: Understanding and Predicting Visual Humor
Arjun Chandrasekaran
Ashwin K. Vijayakumar
Stanislaw Antol
Joey Tianyi Zhou
Dhruv Batra
C. L. Zitnick
Devi Parikh
119
57
0
14 Dec 2015
Origami: A 803 GOp/s/W Convolutional Network Accelerator
Origami: A 803 GOp/s/W Convolutional Network Accelerator
Lukas Cavigelli
Luca Benini
80
152
0
14 Dec 2015
Learning Deep Features for Discriminative Localization
Learning Deep Features for Discriminative Localization
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
SSLSSegFAtt
485
9,365
0
14 Dec 2015
Inside-Outside Net: Detecting Objects in Context with Skip Pooling and
  Recurrent Neural Networks
Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks
Sean Bell
C. L. Zitnick
Kavita Bala
Ross B. Girshick
ObjD
125
1,213
0
14 Dec 2015
Deep Relative Attributes
Deep Relative Attributes
Yaser Souri
Erfan Noury
Ehsan Adeli
GAN3DHOODFAtt
102
105
0
13 Dec 2015
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.9K
195,310
0
10 Dec 2015
Learning to Point and Count
Learning to Point and Count
Jie Shao
Dequan Wang
Xiangyang Xue
Zheng Zhang
70
5
0
08 Dec 2015
SSD: Single Shot MultiBox Detector
SSD: Single Shot MultiBox Detector
Wen Liu
Dragomir Anguelov
D. Erhan
Christian Szegedy
Scott E. Reed
Cheng-Yang Fu
Alexander C. Berg
ObjDBDL
651
30,020
0
08 Dec 2015
Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images
Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images
Aravindh Mahendran
Andrea Vedaldi
FAtt
132
536
0
07 Dec 2015
Sparsifying Neural Network Connections for Face Recognition
Sparsifying Neural Network Connections for Face Recognition
Yi Sun
Xiaogang Wang
Xiaoou Tang
3DHCVBM
89
141
0
07 Dec 2015
A Restricted Visual Turing Test for Deep Scene and Event Understanding
A Restricted Visual Turing Test for Deep Scene and Event Understanding
Qi
Tianfu Wu
M. Lee
Song-Chun Zhu
66
12
0
06 Dec 2015
MXNet: A Flexible and Efficient Machine Learning Library for
  Heterogeneous Distributed Systems
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
Tianqi Chen
Mu Li
Yutian Li
Min Lin
Naiyan Wang
Minjie Wang
Tianjun Xiao
Bing Xu
Chiyuan Zhang
Zheng Zhang
221
2,252
0
03 Dec 2015
Actions ~ Transformations
Actions ~ Transformations
Xinyu Wang
Ali Farhadi
Abhinav Gupta
81
234
0
02 Dec 2015
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DVBDL
1.4K
27,513
0
02 Dec 2015
Loss Functions for Top-k Error: Analysis and Insights
Loss Functions for Top-k Error: Analysis and Insights
Maksim Lapin
Matthias Hein
Bernt Schiele
184
97
0
01 Dec 2015
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks
Sebastian Bach
Alexander Binder
G. Montavon
K. Müller
Wojciech Samek
96
199
0
01 Dec 2015
DenseCap: Fully Convolutional Localization Networks for Dense Captioning
DenseCap: Fully Convolutional Localization Networks for Dense Captioning
Justin Johnson
A. Karpathy
Li Fei-Fei
VLM
156
1,172
0
24 Nov 2015
Where To Look: Focus Regions for Visual Question Answering
Where To Look: Focus Regions for Visual Question Answering
Kevin J. Shih
Saurabh Singh
Derek Hoiem
116
462
0
23 Nov 2015
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints
Eric Tzeng
Coline Devin
Judy Hoffman
Chelsea Finn
Pieter Abbeel
Sergey Levine
Kate Saenko
Trevor Darrell
OOD
130
140
0
23 Nov 2015
End-to-end Learning of Action Detection from Frame Glimpses in Videos
End-to-end Learning of Action Detection from Frame Glimpses in Videos
Serena Yeung
Olga Russakovsky
Greg Mori
Li Fei-Fei
EgoV
158
608
0
22 Nov 2015
Gradual DropIn of Layers to Train Very Deep Neural Networks
Gradual DropIn of Layers to Train Very Deep Neural Networks
L. Smith
Emily M. Hand
T. Doster
AI4CE
91
33
0
22 Nov 2015
Zoom Better to See Clearer: Human and Object Parsing with Hierarchical
  Auto-Zoom Net
Zoom Better to See Clearer: Human and Object Parsing with Hierarchical Auto-Zoom Net
Fangting Xia
Peng Wang
Liang-Chieh Chen
Alan Yuille
159
167
0
21 Nov 2015
Data-dependent Initializations of Convolutional Neural Networks
Data-dependent Initializations of Convolutional Neural Networks
Philipp Krahenbuhl
Carl Doersch
Jeff Donahue
Trevor Darrell
VLM
126
203
0
21 Nov 2015
Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural
  Nets
Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets
T. Narihira
Damian Borth
Stella X. Yu
Karl S. Ni
Trevor Darrell
CoGe
41
14
0
21 Nov 2015
The Unreasonable Effectiveness of Noisy Data for Fine-Grained
  Recognition
The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition
J. Krause
Benjamin Sapp
Andrew Howard
Howard Zhou
Alexander Toshev
Tom Duerig
James Philbin
Fei-Fei Li
94
364
0
20 Nov 2015
Top-k Multiclass SVM
Top-k Multiclass SVM
Maksim Lapin
Matthias Hein
Bernt Schiele
VLM
81
92
0
20 Nov 2015
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
FedMLSSLDML
199
1,650
0
19 Nov 2015
A convnet for non-maximum suppression
A convnet for non-maximum suppression
J. Hosang
Rodrigo Benenson
Bernt Schiele
80
76
0
19 Nov 2015
Comparative Study of Deep Learning Software Frameworks
Comparative Study of Deep Learning Software Frameworks
S. Bahrampour
Naveen Ramakrishnan
Lukas Schott
Mohak Shah
109
161
0
19 Nov 2015
All you need is a good init
All you need is a good init
Dmytro Mishkin
Jirí Matas
ODL
148
612
0
19 Nov 2015
Deep Manifold Traversal: Changing Labels with Convolutional Features
Deep Manifold Traversal: Changing Labels with Convolutional Features
Jacob R. Gardner
P. Upchurch
Matt J. Kusner
Yixuan Li
Kilian Q. Weinberger
Kavita Bala
John E. Hopcroft
90
67
0
19 Nov 2015
QBDC: Query by dropout committee for training deep supervised
  architecture
QBDC: Query by dropout committee for training deep supervised architecture
Mélanie Ducoffe
F. Precioso
OODMU
46
19
0
19 Nov 2015
Training Deep Neural Networks via Direct Loss Minimization
Training Deep Neural Networks via Direct Loss Minimization
Yang Song
Alex Schwing
R. Zemel
R. Urtasun
92
102
0
19 Nov 2015
Why M Heads are Better than One: Training a Diverse Ensemble of Deep
  Networks
Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks
Stefan Lee
Senthil Purushwalkam
Michael Cogswell
David J. Crandall
Dhruv Batra
FedMLUQCV
116
316
0
19 Nov 2015
Robust Convolutional Neural Networks under Adversarial Noise
Robust Convolutional Neural Networks under Adversarial Noise
Jonghoon Jin
Aysegül Dündar
Eugenio Culurciello
88
77
0
19 Nov 2015
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