Fetching the paper…
Reading the bibliography…
Given a grayscale photograph as input, this paper attacks the problem of hallucinating a plausible color version of the photograph.
Learning hierarchical features for scene labeling
Farabet, C., Couprie, C., Najman, L., LeCun, Y.: · 1929
Earlier work this paper cites.
Optimization by simmulated annealing
Kirkpatrick, S., Vecchi, M.P., et al.: · 1983
Earlier work this paper cites.
Bootstrap methods: another look at the jackknife
Efron, B.: · 1992
Earlier work this paper cites.
Image analogies
Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B., Salesin, D.H.: · 2001
Earlier work this paper cites.
Transferring color to greyscale images
Welsh, T., Ashikhmin, M., Mueller, K.: · 2002
Earlier work this paper cites.
Visual equivalence: towards a new standard for image fidelity
Ramanarayanan, G., Ferwerda, J., Walter, B., Bala, K.: · 2007
Earlier work this paper cites.
The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results
Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: · 2007
Earlier work this paper cites.
Automatic image colorization via multimodal predictions
Charpiat, G., Hofmann, M., Schölkopf, B.: · 2008
Earlier work this paper cites.
Intrinsic colorization
Liu, X., Wan, L., Qu, Y., Wong, T.T., Lin, S., Leung, C.S., Heng, P.A.: · 2008
Earlier work this paper cites.
Learning to search: Functional gradient techniques for imitation learning
Ratliff, N.D., Silver, D., Bagnell, J.A.: · 2009
Earlier work this paper cites.
The pascal visual object classes (voc) challenge
Everingham, M., Van Gool, L., Williams, C.K., Winn, J., Zisserman, A.: · 2010
Earlier work this paper cites.
Sun database: Large-scale scene recognition from abbey to zoo
Xiao, J., Hays, J., Ehinger, K.A., Oliva, A., Torralba, A.: · 2010
Earlier work this paper cites.
Multimodal deep learning
Ngiam, J., Khosla, A., Kim, M., Nam, J., Lee, H., Ng, A.Y.: · 2011
Earlier work this paper cites.
Semantic colorization with internet images
Chia, A.Y.S., Zhuo, S., Gupta, R.K., Tai, Y.W., Cho, S.Y., Tan, P., Lin, S.: · 2011
Earlier work this paper cites.
Image colorization using similar images
Gupta, R.K., Chia, A.Y.S., Rajan, D., Ng, E.S., Zhiyong, H.: · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
Earlier work this paper cites.
The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: · 2012
Cited alongside, same era.
Representation learning: A review and new perspectives
Bengio, Y., Courville, A., Vincent, P.: · 2013
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2014
Cited alongside, same era.
Learning deep features for scene recognition using places database
Zhou, B., Lapedriza, A., Xiao, J., Torralba, A., Oliva, A.: · 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.
Deep colorization
Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., Darrell, T.: · 2015
Later among the works it cites.
Color constancy by learning to predict chromaticity from luminance
Chakrabarti, A.: · 2015
Later among the works it cites.
Automatic colorization
Dahl, R.: · 2016
Closest in time.
Context encoders: Feature learning by inpainting
Pathak, D., Krähenbühl, P., Donahue, J., Darrell, T., Efros, A.: · 2016
Closest in time.
Deep predictive coding networks for video prediction and unsupervised learning
Lotter, W., Kreiman, G., Cox, D.: · 2016
Closest in time.
Visually indicated sounds
Owens, A., Isola, P., McDermott, J., Torralba, A., Adelson, E.H., Freeman, W.T.: · 2016
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cheng, Z., Yang, Q., Sheng, B.: · 2015
Cited alongside, same era.
Learning to see by moving
Agrawal, P., Carreira, J., Malik, J.: · 2015
Cited alongside, same era.
Learning image representations tied to ego-motion
Jayaraman, D., Grauman, K.: · 2015
Cited alongside, same era.
Unsupervised visual representation learning by context prediction
Doersch, C., Gupta, A., Efros, A.A.: · 2015
Cited alongside, same era.
Unsupervised learning of visual representations using videos
Wang, X., Gupta, A.: · 2015
Cited alongside, same era.
Learning large-scale automatic image colorization
Deshpande, A., Rock, J., Forsyth, D.: · 2015
Cited alongside, same era.
Hypercolumns for object segmentation and fine-grained localization
Hariharan, B., Arbeláez, P., Girshick, R., Malik, J.: · 2015
Cited alongside, same era.
Ambient sound provides supervision for visual learning
Owens, A., Wu, J., McDermott, J.H., Freeman, W.T., Torralba, A.: · 2016
Closest in time.
Donahue, J., Krähenbühl, P., Darrell, T.: · 2016
Closest in time.
Learning representations for automatic colorization
Larsson, G., Maire, M., Shakhnarovich, G.: · 2016
Closest in time.
Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification
Iizuka, S., Simo-Serra, E., Ishikawa, H.: · 2016
Closest in time.
Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: · 2016
Closest in time.
Multi-scale context aggregation by dilated convolutions
Yu, F., Koltun, V.: · 2016
Closest in time.
Data-dependent initializations of convolutional neural networks
Krähenbühl, P., Doersch, C., Donahue, J., Darrell, T.: · 2016
Closest in time.
Unsupervised learning of visual representations by solving jigsaw puzzles
Noroozi, M., Favaro, P.: · 2016
Closest in time.
Sun attribute database: Discovering, annotating, and recognizing scene attributes
Patterson, G., Hays, J.: · 2016
Closest in time.