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Hierarchy-based Image Embeddings for Semantic Image Retrieval

Hierarchy-based Image Embeddings for Semantic Image Retrieval

26 September 2018
Björn Barz
Joachim Denzler
    SSL
ArXivPDFHTML

Papers citing "Hierarchy-based Image Embeddings for Semantic Image Retrieval"

19 / 19 papers shown
Title
HELM: Hierarchical Encoding for mRNA Language Modeling
HELM: Hierarchical Encoding for mRNA Language Modeling
Mehdi Yazdani-Jahromi
Mangal Prakash
Tommaso Mansi
Artem Moskalev
Rui Liao
114
3
0
13 Mar 2025
Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport
Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport
Siqi Zeng
Sixian Du
M. Yamada
Han Zhao
OT
57
1
0
04 Oct 2024
Significance of Softmax-based Features in Comparison to Distance Metric
  Learning-based Features
Significance of Softmax-based Features in Comparison to Distance Metric Learning-based Features
Shota Horiguchi
Daiki Ikami
Kiyoharu Aizawa
37
64
0
29 Dec 2017
Label Embedding Network: Learning Label Representation for Soft Training
  of Deep Networks
Label Embedding Network: Learning Label Representation for Soft Training of Deep Networks
Xu Sun
Bingzhen Wei
Xuancheng Ren
Shuming Ma
42
40
0
28 Oct 2017
Random Erasing Data Augmentation
Random Erasing Data Augmentation
Zhun Zhong
Liang Zheng
Guoliang Kang
Shaozi Li
Yi Yang
63
3,614
0
16 Aug 2017
Learning Structured Semantic Embeddings for Visual Recognition
Learning Structured Semantic Embeddings for Visual Recognition
Dong Li
Hsin-Ying Lee
Jia-Bin Huang
Shengjin Wang
Ming-Hsuan Yang
32
9
0
05 Jun 2017
Beyond triplet loss: a deep quadruplet network for person
  re-identification
Beyond triplet loss: a deep quadruplet network for person re-identification
Weihua Chen
Xiaotang Chen
Jianguo Zhang
Kaiqi Huang
61
1,138
0
06 Apr 2017
YOLO9000: Better, Faster, Stronger
YOLO9000: Better, Faster, Stronger
Joseph Redmon
Ali Farhadi
VLM
ObjD
129
15,535
0
25 Dec 2016
Deep Pyramidal Residual Networks
Deep Pyramidal Residual Networks
Dongyoon Han
Jiwhan Kim
Junmo Kim
60
690
0
10 Oct 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
552
36,599
0
25 Aug 2016
SGDR: Stochastic Gradient Descent with Warm Restarts
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
194
8,030
0
13 Aug 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.0K
192,638
0
10 Dec 2015
Aggregating Deep Convolutional Features for Image Retrieval
Aggregating Deep Convolutional Features for Image Retrieval
Artem Babenko
Victor Lempitsky
FAtt
42
691
0
26 Oct 2015
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
3DH
222
13,079
0
12 Mar 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
655
99,991
0
04 Sep 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
843
39,383
0
01 Sep 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
96
4,936
0
23 Mar 2014
Distributed Representations of Words and Phrases and their
  Compositionality
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAI
OCL
232
33,445
0
16 Oct 2013
On the difficulty of training Recurrent Neural Networks
On the difficulty of training Recurrent Neural Networks
Razvan Pascanu
Tomas Mikolov
Yoshua Bengio
ODL
95
5,318
0
21 Nov 2012
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