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The semantic image segmentation task presents a trade-off between test time accuracy and training-time annotation cost.
Object recognition via recognition of finger pointing actions
Hild, M., Hashimoto, M., Yoshida, K.: · 2003
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GrabCut: Interactive Foreground Extraction Using Iterated Graph Cuts
Rother, C., Kolmogorov, V., Blake, A.: · 2004
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Coordinating with each other in a material world
Clark, H.H.: · 2005
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Augmenting Looking, Pointing and Reaching Gestures to Enhance the Searching and Browsing of Physical Objects
Merrill, D., Maes, P.: · 2007
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The Pascal Visual Object Classes (VOC) challenge
Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: · 2010
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Discriminative Clustering for Image Co-segmentation
Joulin, A., Bach, F., Ponce, J.: · 2010
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Weakly Supervised Semantic Segmentation with a Multi-image Model
Vezhnevets, A., Ferrari, V., Buhmann, J.: · 2011
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BiCoS: A Bi-level Co-Segmentation Method for Image Classification
Chai, Y., Lempitsky, V., Zisserman, A.: · 2011
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Semantic contours from inverse detectors
Hariharan, B., Arbelaez, P., Bourdev, L., Maji, S., Malik, J.: · 2011
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Multiclass Pixel Labeling with Non-Local Matching Constraints
Gould, S.: · 2012
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Weakly Supervised Structured Output Learning for Semantic Segmentation
Vezhnevets, A., Ferrari, V., Buhmann, J.: · 2012
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Measuring the objectness of image windows
Alexe, B., Deselares, T., Ferrari, V.: · 2012
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Learning Hierarchical Features for Scene Labeling
Farabet, C., Couprie, C., Najman, L., LeCun, Y.: · 2013
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Predicting Sufficient Annotation Strength for Interactive Foreground Segmentation
Jain, S.D., Grauman, K.: · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
Girshick, R., Donahue, J., Darrell, T., Malik., J.: · 2014
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TouchCut: Fast Image and Video Segmentation using Single-Touch Interaction
Wang, T., Han, B., Collomosse, J.: · 2014
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Microsoft COCO: Common Objects in Context
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: · 2014
Cited alongside, same era.
On learning to localize objects with minimal supervision
Song, H.O., Girshick, R., Jegelka, S., Mairal, J., Harchaoui, Z., Darrell, T.: · 2014
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Tell Me What You See and I will Show You Where It Is
Xu, J., Schwing, A.G., Urtasun, R.: · 2014
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Training Object Class Detectors from Eye Tracking Data
Papadopoulos, D.P., Clarke, A.D.F., Keller, F., Ferrari, V.: · 2014
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., et al.: · 2015
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Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K., Zisserman, A.: · 2015
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ImageNet Auto-annotation with Segmentation Propagation
Guillaumin, M., Kuettel, D., Ferrari, V.: · 2015
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Learning to Segment Under Various Forms of Weak Supervision
Xu, J., Schwing, A.G., Urtasun, R.: · 2015
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Material Recognition in the Wild with the Materials in Context Database
Bell, S., Upchurch, P., Snavely, N., Bala, K.: · 2015
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Fully Convolutional Multi-Class Multiple Instance Learning
Pathak, D., Shelhamer, E., Long, J., Darrell, T.: · 2015
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Semantic Object Selection
Ahmed, E., Cohen, S., Price, B.: · 2014
Cited alongside, same era.
Please Tap the Shape, Anywhere You Like: Shape skeletons in human vision revealed by an exceedingly simple measure
Firestone, C., Scholl, B.J.: · 2014
Cited alongside, same era.
Robot Deictics: How Gesture and Context Shape Referential Communication
Sauppé, A., Mutlu, B.: · 2014
Cited alongside, same era.
Simultaneous Detection and Segmentation
Hariharan, B., Arbeláez, P., Girshick, R., Malik, J.: · 2014
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., Darrell, T.: · 2014
Cited alongside, same era.
Weakly- and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation
Papandreou, G., Chen, L.C., Murphy, K., Yuille, A.L.: · 2015
Cited alongside, same era.
From Image-level to Pixel-level Labeling with Convolutional Networks
Pinheiro, P.O., Collobert, R.: · 2015
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Decoupled deep neural network for semi-supervised semantic segmentation
Hong, S., Noh, H., Han, B.: · 2015
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Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Dai, J., He, K., Sun, J.: · 2015
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Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: · 2015
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Learning Deconvolution Network for Semantic Segmentation
Noh, H., Hong, S., Han, B.: · 2015
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Best of both worlds: human-machine collaboration for object annotation
Russakovsky, O., Li, L.J., Fei-Fei, L.: · 2015
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ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation
Lin, D., Dai, J., Jia, J., He, K., Sun, J.: · 2016
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