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Found 5 papers, 1 papers with code
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
In this work, we connect two distinct concepts for unsupervised domain adaptation: feature distribution alignment between domains by utilizing the task-specific decision boundary and the Wasserstein metric.
Ranked #19 on
Image-to-Image Translation
on SYNTHIA-to-Cityscapes
Learning to Inpaint for Image Compression
We study the design of deep architectures for lossy image compression.
Multiple Hypothesis Colorization
In the experiments we show that our proposed method outperforms traditional JPEG color coding by a large margin, producing colors that are nearly indistinguishable from the ground truth at the storage cost of just a few hundred bytes for high-resolution pictures!
Network of Experts for Large-Scale Image Categorization
The training of our "network of experts" is completely end-to-end: the partition of categories into disjoint subsets is learned simultaneously with the parameters of the network trunk and the experts are trained jointly by minimizing a single learning objective over all classes.
Coupled Depth Learning
Crucially, the depth basis and the regression function are {\bf coupled} and jointly optimized by our learning scheme.
