ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1903.08923
  4. Cited By
Learning with Batch-wise Optimal Transport Loss for 3D Shape Recognition

Learning with Batch-wise Optimal Transport Loss for 3D Shape Recognition

21 March 2019
Lin Xu
Han Sun
Yuai Liu
    3DPC
ArXiv (abs)PDFHTML

Papers citing "Learning with Batch-wise Optimal Transport Loss for 3D Shape Recognition"

17 / 17 papers shown
Title
GIFT: A Real-time and Scalable 3D Shape Search Engine
GIFT: A Real-time and Scalable 3D Shape Search Engine
S. Bai
X. Bai
Zhichao Zhou
Zhaoxiang Zhang
Longin Jan Latecki
49
281
0
07 Apr 2016
Fine-grained Categorization and Dataset Bootstrapping using Deep Metric
  Learning with Humans in the Loop
Fine-grained Categorization and Dataset Bootstrapping using Deep Metric Learning with Humans in the Loop
Huayu Chen
Feng Zhou
Yuanqing Lin
Serge J. Belongie
90
236
0
16 Dec 2015
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.3K
194,641
0
10 Dec 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
100
1,646
0
19 Nov 2015
Learning with a Wasserstein Loss
Learning with a Wasserstein Loss
Charlie Frogner
Chiyuan Zhang
H. Mobahi
Mauricio Araya-Polo
T. Poggio
83
602
0
17 Jun 2015
Multi-view Convolutional Neural Networks for 3D Shape Recognition
Multi-view Convolutional Neural Networks for 3D Shape Recognition
Hang Su
Subhransu Maji
E. Kalogerakis
Erik Learned-Miller
3DV
173
3,223
0
05 May 2015
Sketch-based 3D Shape Retrieval using Convolutional Neural Networks
Sketch-based 3D Shape Retrieval using Convolutional Neural Networks
Fang Wang
Le Kang
Yi Li
3DV3DPC
63
361
0
14 Apr 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
393
13,172
0
12 Mar 2015
Deep metric learning using Triplet network
Deep metric learning using Triplet network
Elad Hoffer
Nir Ailon
SSLDML
215
2,000
0
20 Dec 2014
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
496
43,717
0
17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,575
0
04 Sep 2014
Learning Fine-grained Image Similarity with Deep Ranking
Learning Fine-grained Image Similarity with Deep Ranking
Jiang Wang
Yang Song
Thomas Leung
C. Rosenberg
Jingbin Wang
James Philbin
Bo Chen
Ying Nian Wu
SSL
120
1,318
0
17 Apr 2014
Rich feature hierarchies for accurate object detection and semantic
  segmentation
Rich feature hierarchies for accurate object detection and semantic segmentation
Ross B. Girshick
Jeff Donahue
Trevor Darrell
Jitendra Malik
ObjD
301
26,223
0
11 Nov 2013
Fast Computation of Wasserstein Barycenters
Fast Computation of Wasserstein Barycenters
Marco Cuturi
Arnaud Doucet
OT
126
743
0
16 Oct 2013
DeCAF: A Deep Convolutional Activation Feature for Generic Visual
  Recognition
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Jeff Donahue
Yangqing Jia
Oriol Vinyals
Judy Hoffman
Ning Zhang
Eric Tzeng
Trevor Darrell
VLMObjD
193
4,954
0
06 Oct 2013
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation
  Distances
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Marco Cuturi
OT
222
4,294
0
04 Jun 2013
Ground Metric Learning
Ground Metric Learning
Marco Cuturi
D. Avis
102
107
0
11 Oct 2011
1