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- University of California, BerkeleyUS183 papers
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- University of ChicagoUS13 papers
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- Lawrence Berkeley National LaboratoryUS10 papers
- Moscow Institute of Thermal TechnologyRU10 papers
- University of MichiganUS10 papers
- University of California, Santa CruzUS9 papers
- Centre National de la Recherche ScientifiqueFR8 papers
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- Michigan Science CenterUS8 papers
12 papers · 1 filter
Learned Dual-View Reflection Removal
Simon Niklaus, Xuaner Cecilia Zhang, Jonathan T. Barron +4
Traditional reflection removal algorithms either use a single image as input, which suffers from intrinsic ambiguities, or use multiple images from a moving camera, which is inconv…
Learning to Factorize and Relight a City
Andrew Liu, Shiry Ginosar, Tinghui Zhou +2
We propose a learning-based framework for disentangling outdoor scenes into temporally-varying illumination and permanent scene factors. Inspired by the classic intrinsic image dec…
Deep Isometric Learning for Visual Recognition
Haozhi Qi, Chong You, Xiaolong Wang +2
Initialization, normalization, and skip connections are believed to be three indispensable techniques for training very deep convolutional neural networks and obtaining state-of-th…
Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation
Arnab Ghosh, Richard Zhang, Puneet K. Dokania +4
We propose an interactive GAN-based sketch-to-image translation method that helps novice users create images of simple objects. As the user starts to draw a sketch of a desired obj…
Zoom To Learn, Learn To Zoom
Xuaner Cecilia Zhang, Qifeng Chen, Ren Ng +1
This paper shows that when applying machine learning to digital zoom for photography, it is beneficial to use real, RAW sensor data for training. Existing learning-based super-reso…
Pushing the Boundaries of View Extrapolation with Multiplane Images
Pratul P. Srinivasan, Richard Tucker, Jonathan T. Barron +3
We explore the problem of view synthesis from a narrow baseline pair of images, and focus on generating high-quality view extrapolations with plausible disocclusions. Our method bu…