Unsupervised Monocular Depth Estimation with Left-Right Consistency | UCL Visual Computing
@inproceedings{monodepth17, title = {Unsupervised Monocular Depth Estimation with Left-Right Consistency}, author = {Cl{\'{e}}ment Godard and Oisin {Mac Aodha} and Gabriel J. Brostow}, booktitle = {CVPR}, year = {2017} } Acknowledgements We would like to thank David Eigen, Ravi Garg, Iro Laina and Fayao Liu for providing data and code to recreate the baseline algorithms. We also thank Stephan Garb
Casual 3D Photography
Our algorithm reconstructs a 3D photo, i.e., a multi-layered panoramic mesh with reconstructed surface color, depth, and normals, from casually captured cell phone or DSLR images. It can be viewed with full binocular and motion parallax in VR as well as on a regular mobile device or in a Web browser. The reconstructed depth and normals allow interacting with the scene through geometry-aware and li
Harmonic Networks: Deep Translation and Rotation Equivariance
Abstract Translating or rotating an input image should not affect the results of many computer vision tasks. Convolutional neural networks (CNNs) are already translation equivariant: input image translations produce proportionate feature map translations. This is not the case for rotations. Global rotation equivariance is typically sought through data augmentation, but patch-wise equivariance is m
Harmonic Networks: Deep Translation and Rotation Equivariance
Abstract Translating or rotating an input image should not affect the results of many computer vision tasks. Convolutional neural networks (CNNs) are already translation equivariant: input image translations produce proportionate feature map translations. This is not the case for rotations. Global rotation equivariance is typically sought through data augmentation, but patch-wise equivariance is m
My Text in Your Handwriting | UCL Visual Computing
There are many scenarios where we wish to imitate a specific author's pen-on-paper handwriting style. Rendering new text in someone's handwriting is difficult because natural handwriting is highly variable, yet follows both intentional and involuntary structure that makes a person's style self-consistent. We present an algorithm that renders a desired input string in an author's handwriting. An an
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