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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 / 11,116 papers shown
Title
Semantic Understanding of Scenes through the ADE20K Dataset
Semantic Understanding of Scenes through the ADE20K Dataset
Bolei Zhou
Hang Zhao
Xavier Puig
Tete Xiao
Sanja Fidler
Adela Barriuso
Antonio Torralba
SSeg
482
1,905
0
18 Aug 2016
Seeing with Humans: Gaze-Assisted Neural Image Captioning
Seeing with Humans: Gaze-Assisted Neural Image Captioning
Yusuke Sugano
Andreas Bulling
105
68
0
18 Aug 2016
A Holistic Approach for Data-Driven Object Cutout
A Holistic Approach for Data-Driven Object Cutout
Huayong Xu
Yangyan Li
Wenzheng Chen
Dani Lischinski
Daniel Cohen-Or
Baoquan Chen
73
4
0
18 Aug 2016
AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene
  Classification
AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene Classification
Gui-Song Xia
Jingwen Hu
Fan Hu
Baoguang Shi
X. Bai
Yanfei Zhong
Liangpei Zhang
108
1,744
0
18 Aug 2016
IM2CAD
IM2CAD
Hamid Izadinia
Qi Shan
S. M. Seitz
3DV
95
198
0
18 Aug 2016
Scalable Learning of Non-Decomposable Objectives
Scalable Learning of Non-Decomposable Objectives
Elad Eban
Mariano Schain
Alan Mackey
A. Gordon
R. Rifkin
G. Elidan
73
111
0
16 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
482
8,622
0
16 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
79
42
0
15 Aug 2016
Weakly Supervised Object Localization Using Size Estimates
Weakly Supervised Object Localization Using Size Estimates
Miaojing Shi
V. Ferrari
WSOL
100
81
0
15 Aug 2016
About Pyramid Structure in Convolutional Neural Networks
About Pyramid Structure in Convolutional Neural Networks
I. Ullah
A. Petrosino
3DV
94
30
0
14 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
97
18
0
11 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
100
189
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
112
312
0
09 Aug 2016
Convolutional Oriented Boundaries
Convolutional Oriented Boundaries
Kevis-Kokitsi Maninis
Jordi Pont-Tuset
Pablo Arbelaez
Luc Van Gool
92
233
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
94
5
0
09 Aug 2016
Learning Joint Representations of Videos and Sentences with Web Image
  Search
Learning Joint Representations of Videos and Sentences with Web Image Search
Mayu Otani
Yuta Nakashima
Esa Rahtu
J. Heikkilä
N. Yokoya
74
94
0
08 Aug 2016
HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment
HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment
Ivan Vulić
D. Gerz
Douwe Kiela
Felix Hill
Anna Korhonen
111
103
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
107
108
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
108
208
0
04 Aug 2016
Improving Multi-label Learning with Missing Labels by Structured
  Semantic Correlations
Improving Multi-label Learning with Missing Labels by Structured Semantic Correlations
Hao Yang
Qiufeng Wang
Jianfei Cai
105
66
0
04 Aug 2016
A study of the effect of JPG compression on adversarial images
A study of the effect of JPG compression on adversarial images
Gintare Karolina Dziugaite
Zoubin Ghahramani
Daniel M. Roy
AAML
128
537
0
02 Aug 2016
Top-down Neural Attention by Excitation Backprop
Top-down Neural Attention by Excitation Backprop
Jianming Zhang
Zhe Lin
Jonathan Brandt
Xiaohui Shen
Stan Sclaroff
142
949
0
01 Aug 2016
Modeling Context in Referring Expressions
Modeling Context in Referring Expressions
Licheng Yu
Patrick Poirson
Shan Yang
Alexander C. Berg
Tamara L. Berg
170
1,283
0
31 Jul 2016
Can a CNN Recognize Catalan Diet?
Can a CNN Recognize Catalan Diet?
Pedro Herruzo
Marc Bolaños
Petia Radeva
71
4
0
29 Jul 2016
SSDH: Semi-supervised Deep Hashing for Large Scale Image Retrieval
SSDH: Semi-supervised Deep Hashing for Large Scale Image Retrieval
Jian Zhang
Yuxin Peng
96
129
0
28 Jul 2016
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
Yandong Guo
Lei Zhang
Yuxiao Hu
Xiaodong He
Jianfeng Gao
CVBM
339
1,976
0
27 Jul 2016
Region-based semantic segmentation with end-to-end training
Region-based semantic segmentation with end-to-end training
Holger Caesar
J. Uijlings
V. Ferrari
86
82
0
26 Jul 2016
Salient Object Subitizing
Salient Object Subitizing
Jianming Zhang
Shugao Ma
M. Sameki
Stan Sclaroff
Margrit Betke
Zhe Lin
Xiaohui Shen
Brian L. Price
R. Měch
93
115
0
26 Jul 2016
A Unified Multi-scale Deep Convolutional Neural Network for Fast Object
  Detection
A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection
Zhaowei Cai
Quanfu Fan
Rogerio Feris
Nuno Vasconcelos
ObjD
155
1,491
0
25 Jul 2016
Is Faster R-CNN Doing Well for Pedestrian Detection?
Is Faster R-CNN Doing Well for Pedestrian Detection?
Liliang Zhang
Liang Lin
Xiaodan Liang
Kaiming He
ObjD
93
820
0
24 Jul 2016
Geometric Neural Phrase Pooling: Modeling the Spatial Co-occurrence of
  Neurons
Geometric Neural Phrase Pooling: Modeling the Spatial Co-occurrence of Neurons
Lingxi Xie
Qi Tian
John Flynn
Jingdong Wang
Alan Yuille
68
11
0
21 Jul 2016
Dual Purpose Hashing
Dual Purpose Hashing
Haomiao Liu
Ruiping Wang
Shiguang Shan
Xilin Chen
26
1
0
19 Jul 2016
A Real-Time Deep Learning Pedestrian Detector for Robot Navigation
A Real-Time Deep Learning Pedestrian Detector for Robot Navigation
D. Ribeiro
André Mateus
Pedro Miraldo
Jacinto C. Nascimento
54
37
0
15 Jul 2016
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
Song Han
Jeff Pool
Sharan Narang
Huizi Mao
Enhao Gong
...
Peter Vajda
Manohar Paluri
J. Tran
Bryan Catanzaro
W. Dally
CVBM
90
83
0
15 Jul 2016
Do semantic parts emerge in Convolutional Neural Networks?
Do semantic parts emerge in Convolutional Neural Networks?
Abel Gonzalez-Garcia
Davide Modolo
V. Ferrari
217
113
0
13 Jul 2016
End-to-end training of object class detectors for mean average precision
End-to-end training of object class detectors for mean average precision
Paul Henderson
V. Ferrari
ObjD
101
275
0
12 Jul 2016
Network Trimming: A Data-Driven Neuron Pruning Approach towards
  Efficient Deep Architectures
Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures
Hengyuan Hu
Rui Peng
Yu-Wing Tai
Chi-Keung Tang
91
892
0
12 Jul 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILMAAML
922
5,935
0
08 Jul 2016
Zero-Shot Visual Recognition via Bidirectional Latent Embedding
Zero-Shot Visual Recognition via Bidirectional Latent Embedding
Qian Wang
Ke Chen
BDL
151
165
0
07 Jul 2016
Learning the semantic structure of objects from Web supervision
Learning the semantic structure of objects from Web supervision
David Novotny
Diane Larlus
Andrea Vedaldi
OCL
72
7
0
05 Jul 2016
Fully-Convolutional Siamese Networks for Object Tracking
Fully-Convolutional Siamese Networks for Object Tracking
Luca Bertinetto
Jack Valmadre
João F. Henriques
Andrea Vedaldi
Philip Torr
VOT
179
3,901
0
30 Jun 2016
Parking Stall Vacancy Indicator System Based on Deep Convolutional
  Neural Networks
Parking Stall Vacancy Indicator System Based on Deep Convolutional Neural Networks
Sepehr Valipour
Mennatullah Siam
Eleni Stroulia
Martin Jägersand
52
83
0
30 Jun 2016
Learning without Forgetting
Learning without Forgetting
Zhizhong Li
Derek Hoiem
CLLOODSSL
577
4,468
0
29 Jun 2016
A Taxonomy and Library for Visualizing Learned Features in Convolutional
  Neural Networks
A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks
Felix Grün
Christian Rupprecht
Nassir Navab
Federico Tombari
SSLFAtt
73
76
0
24 Jun 2016
CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation
  Tasks
CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks
Jindrich Libovický
Jindřich Helcl
Marek Tlustý
Pavel Pecina
Ondrej Bojar
89
68
0
23 Jun 2016
VideoMCC: a New Benchmark for Video Comprehension
VideoMCC: a New Benchmark for Video Comprehension
Du Tran
Maksim Bolonkin
Manohar Paluri
Lorenzo Torresani
74
1
0
23 Jun 2016
Picture It In Your Mind: Generating High Level Visual Representations
  From Textual Descriptions
Picture It In Your Mind: Generating High Level Visual Representations From Textual Descriptions
F. Carrara
Andrea Esuli
T. Fagni
Fabrizio Falchi
Alejandro Moreo
DiffM
68
30
0
23 Jun 2016
Saliency Driven Object recognition in egocentric videos with deep CNN
Saliency Driven Object recognition in egocentric videos with deep CNN
P. Roman
J. Benois-Pineau
J. Domenger
F. Paclet
D. Cattaert
A. Rugy
92
32
0
23 Jun 2016
Where to Focus: Query Adaptive Matching for Instance Retrieval Using
  Convolutional Feature Maps
Where to Focus: Query Adaptive Matching for Instance Retrieval Using Convolutional Feature Maps
Jiewei Cao
Lingqiao Liu
Peng Wang
Zi Huang
Chunhua Shen
Heng Tao Shen
83
19
0
22 Jun 2016
Past, Present, and Future of Simultaneous Localization And Mapping:
  Towards the Robust-Perception Age
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Cesar Cadena
Luca Carlone
Henry Carrillo
Yasir Latif
Davide Scaramuzza
José Neira
Ian Reid
J. Leonard
262
2,938
0
19 Jun 2016
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