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Rich feature hierarchies for accurate object detection and semantic
  segmentation

Rich feature hierarchies for accurate object detection and semantic segmentation

11 November 2013
Ross B. Girshick
Jeff Donahue
Trevor Darrell
Jitendra Malik
    ObjD
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Papers citing "Rich feature hierarchies for accurate object detection and semantic segmentation"

31 / 3,381 papers shown
Title
Learning Rich Features from RGB-D Images for Object Detection and
  Segmentation
Learning Rich Features from RGB-D Images for Object Detection and Segmentation
Saurabh Gupta
Ross B. Girshick
Pablo Arbeláez
Jitendra Malik
ObjD
68
1,558
0
22 Jul 2014
Pixels to Voxels: Modeling Visual Representation in the Human Brain
Pixels to Voxels: Modeling Visual Representation in the Human Brain
Pulkit Agrawal
D. Stansbury
Jitendra Malik
J. Gallant
29
102
0
18 Jul 2014
LSDA: Large Scale Detection Through Adaptation
LSDA: Large Scale Detection Through Adaptation
Judy Hoffman
S. Guadarrama
Eric Tzeng
Ronghang Hu
Jeff Donahue
Ross B. Girshick
Trevor Darrell
Kate Saenko
ObjD
53
335
0
18 Jul 2014
Part-based R-CNNs for Fine-grained Category Detection
Part-based R-CNNs for Fine-grained Category Detection
Ning Zhang
Jeff Donahue
Ross B. Girshick
Trevor Darrell
ObjD
54
1,223
0
15 Jul 2014
Learning Deep Structured Models
Learning Deep Structured Models
Liang-Chieh Chen
Alex Schwing
Alan Yuille
R. Urtasun
BDL
67
247
0
09 Jul 2014
Simultaneous Detection and Segmentation
Simultaneous Detection and Segmentation
Bharath Hariharan
Pablo Arbeláez
Ross B. Girshick
Jitendra Malik
ObjD
ISeg
69
1,291
0
07 Jul 2014
Analyzing the Performance of Multilayer Neural Networks for Object
  Recognition
Analyzing the Performance of Multilayer Neural Networks for Object Recognition
Pulkit Agrawal
Ross B. Girshick
Jitendra Malik
SSL
66
441
0
07 Jul 2014
How good are detection proposals, really?
How good are detection proposals, really?
J. Hosang
Rodrigo Benenson
Bernt Schiele
ObjD
17
272
0
26 Jun 2014
Deep Learning Multi-View Representation for Face Recognition
Deep Learning Multi-View Representation for Face Recognition
Zhenyao Zhu
Ping Luo
Xiaogang Wang
Xiaoou Tang
CVBM
29
35
0
26 Jun 2014
Recurrent Models of Visual Attention
Recurrent Models of Visual Attention
Volodymyr Mnih
N. Heess
Alex Graves
Koray Kavukcuoglu
VLM
22
3,644
0
24 Jun 2014
Factors of Transferability for a Generic ConvNet Representation
Factors of Transferability for a Generic ConvNet Representation
Hossein Azizpour
A. Razavian
Josephine Sullivan
A. Maki
S. Carlsson
33
421
0
22 Jun 2014
CNN: Single-label to Multi-label
CNN: Single-label to Multi-label
Yunchao Wei
Wei Xia
Junshi Huang
Bingbing Ni
Jian Dong
Yao-Min Zhao
Shuicheng Yan
54
671
0
22 Jun 2014
Caffe: Convolutional Architecture for Fast Feature Embedding
Caffe: Convolutional Architecture for Fast Feature Embedding
Yangqing Jia
Evan Shelhamer
Jeff Donahue
Sergey Karayev
Jonathan Long
Ross B. Girshick
S. Guadarrama
Trevor Darrell
VLM
BDL
3DV
114
14,696
0
20 Jun 2014
R-CNNs for Pose Estimation and Action Detection
R-CNNs for Pose Estimation and Action Detection
Georgia Gkioxari
Bharath Hariharan
Ross B. Girshick
Jitendra Malik
37
159
0
19 Jun 2014
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual
  Recognition
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
ObjD
92
11,156
0
18 Jun 2014
Bird Species Categorization Using Pose Normalized Deep Convolutional
  Nets
Bird Species Categorization Using Pose Normalized Deep Convolutional Nets
Steve Branson
Grant Van Horn
Serge J. Belongie
Pietro Perona
32
512
0
11 Jun 2014
Deep Epitomic Convolutional Neural Networks
Deep Epitomic Convolutional Neural Networks
George Papandreou
50
7
0
10 Jun 2014
Seeing the Big Picture: Deep Embedding with Contextual Evidences
Seeing the Big Picture: Deep Embedding with Contextual Evidences
Liang Zheng
Shengjin Wang
Fei He
Q. Tian
72
20
0
01 Jun 2014
Descriptor Matching with Convolutional Neural Networks: a Comparison to SIFT
Philipp Fischer
Alexey Dosovitskiy
Thomas Brox
42
276
0
22 May 2014
Return of the Devil in the Details: Delving Deep into Convolutional Nets
Return of the Devil in the Details: Delving Deep into Convolutional Nets
Ken Chatfield
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
111
3,412
0
14 May 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
45
43,044
0
01 May 2014
Generic Object Detection With Dense Neural Patterns and Regionlets
Generic Object Detection With Dense Neural Patterns and Regionlets
Will Y. Zou
Xiaoyu Wang
Miao Sun
Yuanqing Lin
ObjD
49
66
0
16 Apr 2014
DenseNet: Implementing Efficient ConvNet Descriptor Pyramids
DenseNet: Implementing Efficient ConvNet Descriptor Pyramids
F. Iandola
Matthew W. Moskewicz
Sergey Karayev
Ross B. Girshick
Trevor Darrell
Kurt Keutzer
48
272
0
07 Apr 2014
CNN Features off-the-shelf: an Astounding Baseline for Recognition
CNN Features off-the-shelf: an Astounding Baseline for Recognition
A. Razavian
Hossein Azizpour
Josephine Sullivan
S. Carlsson
64
4,932
0
23 Mar 2014
Rigid-Motion Scattering for Texture Classification
Rigid-Motion Scattering for Texture Classification
Laurent Sifre
S. Mallat
31
343
0
07 Mar 2014
Can Image-Level Labels Replace Pixel-Level Labels for Image Parsing
Can Image-Level Labels Replace Pixel-Level Labels for Image Parsing
Zhiwu Lu
Zhenyong Fu
Tao Xiang
Liwei Wang
Ji-Rong Wen
46
108
0
07 Mar 2014
On learning to localize objects with minimal supervision
On learning to localize objects with minimal supervision
Hyun Oh Song
Ross B. Girshick
Stefanie Jegelka
Julien Mairal
Zaïd Harchaoui
Trevor Darrell
49
250
0
05 Mar 2014
One-Shot Adaptation of Supervised Deep Convolutional Models
One-Shot Adaptation of Supervised Deep Convolutional Models
Judy Hoffman
Eric Tzeng
Jeff Donahue
Yangqing Jia
Kate Saenko
Trevor Darrell
OOD
40
80
0
21 Dec 2013
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network
  Training
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training
T. Paine
Hailin Jin
Jianchao Yang
Zhe Lin
Thomas Huang
54
99
0
21 Dec 2013
My First Deep Learning System of 1991 + Deep Learning Timeline 1962-2013
My First Deep Learning System of 1991 + Deep Learning Timeline 1962-2013
Jürgen Schmidhuber
3DGS
PINN
AI4TS
AI4CE
56
12
0
19 Dec 2013
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
34
15,805
0
12 Nov 2013
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