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Manually annotating object bounding boxes is central to building computer vision datasets, and it is very time consuming (annotating ILSVRC [53] took 35s for one high-quality box [62]).
Mental rotation of three-dimensional objects
R. N. Shepard and J. Metzler · 1971
Earlier work this paper cites.
Topographic representations of mental images in primary visual cortex
S. M. Kosslyn, W. L. Thompson, I. J. Kim, and N. M. Alpert · 1995
Earlier work this paper cites.
Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images
Y. Boykov and M. P. Jolly · 2001
Earlier work this paper cites.
Executive control of cognitive processes in task switching
J. S. Rubinstein, D. E. Meyer, and J. E. Evans · 2001
Earlier work this paper cites.
Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary
P. Duygulu, K. Barnard, N. de Freitas, and D. Forsyth · 2002
Earlier work this paper cites.
Task switching
S. Monsell · 2003
Earlier work this paper cites.
Interactive image segmentation using an adaptive GMMRF model
A. Blake, C. Rother, M. Brown, P. Perez, and P. Torr · 2004
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An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision
Y. Boykov and V. Kolmogorov · 2004
Earlier work this paper cites.
Grabcut: Interactive foreground extraction using iterated graph cuts
C. Rother, V. Kolmogorov, and A. Blake · 2004
Earlier work this paper cites.
Interactive graph cut based segmentation with shape priors
D. Freedman and T. Zhang · 2005
Earlier work this paper cites.
An iterative optimization approach for unified image segmentation and matting
J. Wang and M. Cohen · 2005
Earlier work this paper cites.
Random walks for image segmentation
L. Grady · 2006
Earlier work this paper cites.
Contextual guidance of attention in natural scenes: The role of global features on object search
A. Torralba, A. Oliva, M. Castelhano, and J. M. Henderson · 2006
Earlier work this paper cites.
The PASCAL Visual Object Classes Challenge 2007 Results, 2007
M. Everingham, L. Van Gool, C. Williams, J. Winn, and A. Zisserman · 2007
Earlier work this paper cites.
Segmentation by transduction
O. Duchenne, J.-Y. Audibert, R. Keriven, J. Ponce, and F. Ségonne · 2008
Earlier work this paper cites.
Progressive search space reduction for human pose estimation
V. Ferrari, M. Marin, and A. Zisserman · 2008
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Beyond nouns: Exploiting prepositions and comparators for learning visual classifiers
A. Gupta and L. Davis · 2008
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LabelMe: a database and web-based tool for image annotation
B. C. Russell, K. P. Murphy, and W. T. Freeman · 2008
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Utility data annotation with amazon mechanical turk
A. Sorokin and D. Forsyth · 2008
Earlier work this paper cites.
Star shape prior for graph-cut image segmentation
O. Veksler · 2008
Earlier work this paper cites.
Graph cut based image segmentation with connectivity priors
S. Vicente, V. Kolmogorov, and C. Rother · 2008
Earlier work this paper cites.
Geodesic matting: A framework for fast interactive image and video segmentation and matting
X. Bai and G. Sapiro · 2009
Earlier work this paper cites.
ImageNet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-fei · 2009
Earlier work this paper cites.
Modelling search for people in 900 scenes: A combined source model of eye guidance
K. A. Ehinger, B. Hidalgo-Sotelo, A. Torralba, and A. Olivia · 2009
Earlier work this paper cites.
Image segmentation with a bounding box prior
V. Lempitsky, P. Kohli, C. Rother, and T. Sharp · 2009
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The benefits and challenges of collecting richer object annotations
I. Endres, A. Farhadi, D. Hoiem, and D. A. Forsyth · 2010
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The PASCAL Visual Object Classes (VOC) Challenge
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
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V. Gulshan, C. Rother, A. Criminisi, A. Blake, and A. Zisserman · 2010
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B. L. Price, B. Morse, and S. Cohen · 2010
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The multidimensional wisdom of crowds
P. Welinder, S. Branson, P. Perona, and S. J. Belongie · 2010
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2d human pose estimation: New benchmark and state of the art analysis
M. Andriluka, L. Pishchulin, P. Gehler, and B. Schiele · 2014
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Microsoft COCO: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. Zitnick · 2014
Later among the works it cites.
Training object class detectors from eye tracking data
D. P. Papadopoulos, A. D. F. Clarke, F. Keller, and V. Ferrari · 2014
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Touchcut: Fast image and video segmentation using single-touch interaction
T. Wang, B. Han, and J. Collomosse · 2014
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Milcut: A sweeping line multiple instance learning paradigm for interactive image segmentation
J. Wu, Y. Zhao, J.-Y. Zhu, S. Luo, and Z. Tu · 2014
Later among the works it cites.
Semantic image segmentation with deep convolutional nets and fully connected CRFs
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P. Arbeláez, M. Maire, C. Fowlkes, and J. Malik · 2011
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G. Papandreou, L.-C. Chen, K. Murphy, and A. L. Yuille · 2015
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O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. Berg, and L. Fei-Fei · 2015
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Best of both worlds: human-machine collaboration for object annotation
O. Russakovsky, L.-J. Li, and L. Fei-Fei · 2015
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Very deep convolutional networks for large-scale image recognition
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Large-scale weakly supervised object localization via latent category learning
C. Wang, W. Ren, J. Zhang, K. Huang, and S. Maybank · 2015
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What’s the point: Semantic segmentation with point supervision
A. Bearman, O. Russakovsky, V. Ferrari, and L. Fei-Fei · 2016
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Weakly supervised deep detection networks
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Weakly supervised object localization with multi-fold multiple instance learning
R. Cinbis, J. Verbeek, and C. Schmid · 2016
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Crowdflower bounding box annotation tool
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Click carving: Segmenting objects in video with point clicks
S. Jain and K. Grauman · 2016
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Analysing domain shift factors between videos and images for object detection
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Track and transfer: Watching videos to simulate strong human supervision for weakly-supervised object detection
K. Kumar Singh, F. Xiao, and Y. Jae Lee · 2016
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We don’t need no bounding-boxes: Training object class detectors using only human verification
D. P. Papadopoulos, J. R. R. Uijlings, F. Keller, and V. Ferrari · 2016
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A glimpse far into the future: Understanding long-term crowd worker accuracy
K. Hata, R. Krishna, L. Fei-Fei, and M. Bernstain · 2017
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