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Found 5 papers, 3 papers with code
Self-Supervised Relative Depth Learning for Urban Scene Understanding
As an agent moves through the world, the apparent motion of scene elements is (usually) inversely proportional to their depth.
Discovery of Visual Semantics by Unsupervised and Self-Supervised Representation Learning
The success of deep learning in computer vision is rooted in the ability of deep networks to scale up model complexity as demanded by challenging visual tasks.
FractalNet: Ultra-Deep Neural Networks without Residuals
We introduce a design strategy for neural network macro-architecture based on self-similarity.
Ranked #29 on
Image Classification
on SVHN
Learning Representations for Automatic Colorization
This intermediate output can be used to automatically generate a color image, or further manipulated prior to image formation.
