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. 1511.07803
  4. Cited By
Weakly Supervised Object Boundaries

Weakly Supervised Object Boundaries

24 November 2015
Anna Khoreva
Rodrigo Benenson
Mohamed Omran
Matthias Hein
Bernt Schiele
ArXivPDFHTML

Papers citing "Weakly Supervised Object Boundaries"

17 / 17 papers shown
Title
Unsupervised Learning of Edges
Unsupervised Learning of Edges
Yin Li
Manohar Paluri
James M. Rehg
Piotr Dollár
SSL
53
91
0
13 Nov 2015
Semantic Segmentation with Boundary Neural Fields
Semantic Segmentation with Boundary Neural Fields
Gedas Bertasius
Jianbo Shi
Lorenzo Torresani
53
191
0
09 Nov 2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal
  Networks
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren
Kaiming He
Ross B. Girshick
Jian Sun
AIMat
ObjD
465
62,122
0
04 Jun 2015
Fast R-CNN
Fast R-CNN
Ross B. Girshick
ObjD
290
25,033
0
30 Apr 2015
Situational Object Boundary Detection
Situational Object Boundary Detection
J. Uijlings
V. Ferrari
57
29
0
24 Apr 2015
Holistically-Nested Edge Detection
Holistically-Nested Edge Detection
Saining Xie
Zhuowen Tu
109
3,484
0
24 Apr 2015
High-for-Low and Low-for-High: Efficient Boundary Detection from Deep
  Object Features and its Applications to High-Level Vision
High-for-Low and Low-for-High: Efficient Boundary Detection from Deep Object Features and its Applications to High-Level Vision
Gedas Bertasius
Jianbo Shi
Lorenzo Torresani
55
168
0
23 Apr 2015
Multiscale Combinatorial Grouping for Image Segmentation and Object
  Proposal Generation
Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation
Jordi Pont-Tuset
Pablo Arbeláez
Jonathan T. Barron
F. Marqués
Jitendra Malik
79
570
0
03 Mar 2015
What makes for effective detection proposals?
What makes for effective detection proposals?
J. Hosang
Rodrigo Benenson
Piotr Dollár
Bernt Schiele
ObjD
105
735
0
17 Feb 2015
segDeepM: Exploiting Segmentation and Context in Deep Neural Networks
  for Object Detection
segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection
Yukun Zhu
R. Urtasun
Ruslan Salakhutdinov
Sanja Fidler
ObjD
47
157
0
15 Feb 2015
Oriented Edge Forests for Boundary Detection
Oriented Edge Forests for Boundary Detection
Sam Hallman
Charless C. Fowlkes
49
152
0
13 Dec 2014
DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour
  Detection
DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection
Gedas Bertasius
Jianbo Shi
Lorenzo Torresani
65
467
0
02 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.4K
100,213
0
04 Sep 2014
$ N^4 $-Fields: Neural Network Nearest Neighbor Fields for Image
  Transforms
N4 N^4 N4-Fields: Neural Network Nearest Neighbor Fields for Image Transforms
Yaroslav Ganin
Victor Lempitsky
OOD
74
271
0
25 Jun 2014
Fast Edge Detection Using Structured Forests
Fast Edge Detection Using Structured Forests
Piotr Dollár
C. L. Zitnick
75
931
0
20 Jun 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
371
43,524
0
01 May 2014
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
283
7,279
0
20 Dec 2013
1