Fetching the paper…
Reading the bibliography…
This paper addresses the problem of estimating the depth map of a scene given a single RGB image.
Shape-from-shading: a survey
R. Zhang, P.-S. Tsai, J. E. Cryer, and M. Shah · 1999
Earlier work this paper cites.
Learning depth from stereo
F. H. Sinz, J. Q. Candela, G. H. Bakır, C. E. Rasmussen, and M. O. Franz · 2004
Earlier work this paper cites.
Histograms of oriented gradients for human detection
N. Dalal and B. Triggs · 2005
Earlier work this paper cites.
Geometric context from a single image
D. Hoiem, A. Efros, M. Hebert, et al · 2005
Earlier work this paper cites.
Learning depth from single monocular images
A. Saxena, S. H. Chung, and A. Y. Ng · 2005
Earlier work this paper cites.
A robust hybrid of lasso and ridge regression
A. B. Owen · 2007
Earlier work this paper cites.
Make3d: Learning 3d scene structure from a single still image
A. Saxena, M. Sun, and A. Ng · 2009
Earlier work this paper cites.
Single image depth estimation from predicted semantic labels
B. Liu, S. Gould, and D. Koller · 2010
Earlier work this paper cites.
Sift flow: Dense correspondence across scenes and its applications
C. Liu, J. Yuen, and A. Torralba · 2011
Earlier work this paper cites.
Stereopsis via deep learning
R. Memisevic and C. Conrad · 2011
Earlier work this paper cites.
Structure from motion
R. Szeliski · 2011
Earlier work this paper cites.
Adaptive deconvolutional networks for mid and high level feature learning
M. D. Zeiler, G. W. Taylor, and R. Fergus · 2011
Earlier work this paper cites.
SLIC superpixels compared to state-of-the-art superpixel methods
R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Susstrunk · 2012
Earlier work this paper cites.
Depth extraction from video using non-parametric sampling
K. Karsch, C. Liu, and S. B. Kang · 2012
Earlier work this paper cites.
2d-to-3d image conversion by learning depth from examples
J. Konrad, M. Wang, and P. Ishwar · 2012
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Cited alongside, same era.
Indoor segmentation and support inference from RGBD images
P. K. Nathan Silberman, Derek Hoiem and R. Fergus · 2012
Cited alongside, same era.
Rgb-(d) scene labeling: Features and algorithms
X. Ren, L. Bo, and D. Fox · 2012
Cited alongside, same era.
The vitruvian manifold: Inferring dense correspondences for one-shot human pose estimation
J. Taylor, J. Shotton, T. Sharp, and A. Fitzgibbon · 2012
Cited alongside, same era.
The berhu penalty and the grouped effect
L. Zwald and S. Lambert-Lacroix · 2012
Robust optimization for deep regression
V. Belagiannis, C. Rupprecht, G. Carneiro, and N. Navab · 2015
Later among the works it cites.
Learning to generate chairs with convolutional neural networks
A. Dosovitskiy, J. Tobias Springenberg, and T. Brox · 2015
Later among the works it cites.
Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
D. Eigen and R. Fergus · 2015
Later among the works it cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Later among the works it cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Real-time 3d reconstruction in dynamic scenes using point-based fusion
M. Keller, D. Lefloch, M. Lambers, S. Izadi, T. Weyrich, and A. Kolb · 2013
Cited alongside, same era.
Robust odometry estimation for RGB-D cameras
C. Kerl, J. Sturm, and D. Cremers · 2013
Cited alongside, same era.
Prediction from a single image using a multi-scale deep network
D. Eigen, C. Puhrsch, and R. Fergus · 2014
Cited alongside, same era.
Pulling things out of perspective
L. Ladicky, J. Shi, and M. Pollefeys · 2014
Cited alongside, same era.
Discrete-continuous depth estimation from a single image
M. Liu, M. Salzmann, and X. He · 2014
Cited alongside, same era.
Modeling the shape of the scene: A holistic representation of the spatial envelope
A. Oliva and A. Torralba · 2014
Cited alongside, same era.
B. Li, C. Shen, Y. Dai, A. V. den Hengel, and M. He · 2015
Later among the works it cites.
Deep convolutional neural fields for depth estimation from a single image
F. Liu, C. Shen, and G. Lin · 2015
Later among the works it cites.
Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Later among the works it cites.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
Later among the works it cites.
Depth from focus with your mobile phone
S. Suwajanakorn and C. Hernandez · 2015
Later among the works it cites.
Matconvnet – convolutional neural networks for matlab
A. Vedaldi and K. Lenc · 2015
Later among the works it cites.
Towards unified depth and semantic prediction from a single image
P. Wang, X. Shen, Z. Lin, S. Cohen, B. Price, and A. L. Yuille · 2015
Later among the works it cites.
Monocular depth estimation using neural regression forest
A. Roy and S. Todorovic · 2016
Closest in time.