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This paper studies single-image depth perception in the wild, i.e., recovering depth from a single image taken in unconstrained settings.
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K. Karsch, C. Liu, and S. B. Kang, “Depthtransfer: Depth extraction from video using non-parametric sampling,” TPAMI
2014
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S. Bell, K. Bala, and N. Snavely, “Intrinsic images in the wild,” TOG
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D. Eigen, C. Puhrsch, and R. Fergus, “Depth map prediction from a single image using a multi-scale deep network,” in NIPS
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M. H. Baig, V. Jagadeesh, R. Piramuthu, A. Bhardwaj, W. Di, and N. Sundaresan, “Im2depth: Scalable exemplar based depth transfer,” in WACV
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C. Hane, L. Ladicky, and M. Pollefeys, “Direction matters: Depth estimation with a surface normal classifier,” in CVPR
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E. Shelhamer, J. Barron, and T. Darrell, “Scene intrinsics and depth from a single image,” in ICCV Workshops
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J. Shi, X. Tao, L. Xu, and J. Jia, “Break ames room illusion: depth from general single images,” TOG
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W. Zhuo, M. Salzmann, X. He, and M. Liu, “Indoor scene structure analysis for single image depth estimation,” in CVPR
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Z. Zhang, A. G. Schwing, S. Fidler, and R. Urtasun, “Monocular object instance segmentation and depth ordering with cnns,” in ICCV
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2014
Cited alongside, same era.
F. Liu, C. Shen, and G. Lin, “Deep convolutional neural fields for depth estimation from a single image,” in CVPR
2015
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D. Eigen and R. Fergus, “Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture,” in ICCV
2015
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M. H. Baig and L. Torresani, “Coupled depth learning,” arXiv preprint arXiv:1501.04537
2015
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B. Li, C. Shen, Y. Dai, A. van den Hengel, and M. He, “Depth and surface normal estimation from monocular images using regression on deep features and hierarchical crfs,” in CVPR
2015
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D. Zoran, P. Isola, D. Krishnan, and W. T. Freeman, “Learning ordinal relationships for mid-level vision,” in ICCV
2015
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S. Song, S. P. Lichtenberg, and J. Xiao, “Sun rgb-d: A rgb-d scene understanding benchmark suite,” in CVPR
2015
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P. Wang, X. Shen, Z. Lin, S. Cohen, B. Price, and A. L. Yuille, “Towards unified depth and semantic prediction from a single image,” in CVPR
2015
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T. Zhou, P. Krahenbuhl, and A. A. Efros, “Learning data-driven reflectance priors for intrinsic image decomposition,” in ICCV
2015
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T. Narihira, M. Maire, and S. X. Yu, “Learning lightness from human judgement on relative reflectance,” in CVPR
2015
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J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in CVPR
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S. Xie and Z. Tu, “Holistically-nested edge detection,” CoRR
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C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in CVPR
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2016
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