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. 1708.02750
  4. Cited By
Extreme clicking for efficient object annotation

Extreme clicking for efficient object annotation

9 August 2017
Dim P. Papadopoulos
J. Uijlings
Frank Keller
V. Ferrari
ArXivPDFHTML

Papers citing "Extreme clicking for efficient object annotation"

16 / 16 papers shown
Title
Feedback-driven object detection and iterative model improvement
Feedback-driven object detection and iterative model improvement
Sönke Tenckhoff
Mario Koddenbrock
Erik Rodner
ObjD
VLM
117
0
0
29 Nov 2024
A Glimpse Far into the Future: Understanding Long-term Crowd Worker
  Quality
A Glimpse Far into the Future: Understanding Long-term Crowd Worker Quality
Kenji Hata
Ranjay Krishna
Fei-Fei Li
Michael S. Bernstein
76
42
0
15 Sep 2016
Click Carving: Segmenting Objects in Video with Point Clicks
Click Carving: Segmenting Objects in Video with Point Clicks
S. Jain
Kristen Grauman
38
54
0
05 Jul 2016
Track and Transfer: Watching Videos to Simulate Strong Human Supervision
  for Weakly-Supervised Object Detection
Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detection
Krishna Kumar Singh
Fanyi Xiao
Yong Jae Lee
28
67
0
19 Apr 2016
We don't need no bounding-boxes: Training object class detectors using
  only human verification
We don't need no bounding-boxes: Training object class detectors using only human verification
Dim P. Papadopoulos
J. Uijlings
Frank Keller
V. Ferrari
VLM
ObjD
39
138
0
26 Feb 2016
Weakly Supervised Deep Detection Networks
Weakly Supervised Deep Detection Networks
Hakan Bilen
Andrea Vedaldi
WSOD
39
784
0
09 Nov 2015
What's the Point: Semantic Segmentation with Point Supervision
What's the Point: Semantic Segmentation with Point Supervision
Amy Bearman
Olga Russakovsky
V. Ferrari
Li Fei-Fei
3DPC
66
983
0
06 Jun 2015
Discovering Attribute Shades of Meaning with the Crowd
Discovering Attribute Shades of Meaning with the Crowd
Adriana Kovashka
Kristen Grauman
FAtt
20
40
0
15 May 2015
Fast R-CNN
Fast R-CNN
Ross B. Girshick
ObjD
247
24,933
0
30 Apr 2015
Weakly Supervised Object Localization with Multi-fold Multiple Instance
  Learning
Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning
R. G. Cinbis
Jakob Verbeek
Cordelia Schmid
WSOD
SSL
48
430
0
03 Mar 2015
Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image
  Segmentation
Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation
George Papandreou
Liang-Chieh Chen
Kevin Patrick Murphy
Alan Yuille
SSeg
72
916
0
09 Feb 2015
Analysing domain shift factors between videos and images for object
  detection
Analysing domain shift factors between videos and images for object detection
Vicky Kalogeiton
V. Ferrari
Cordelia Schmid
50
67
0
06 Jan 2015
Semantic Image Segmentation with Deep Convolutional Nets and Fully
  Connected CRFs
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Liang-Chieh Chen
George Papandreou
Iasonas Kokkinos
Kevin Patrick Murphy
Alan Yuille
SSeg
82
4,882
0
22 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
746
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
909
39,383
0
01 Sep 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
204
43,290
0
01 May 2014
1