Search Results for author:
Found 3 papers, 1 papers with code
Enhancing Generic Segmentation with Learned Region Representations
This representation is combined with an edge map to yield a new segmentation algorithm.
Learning Pixel Representations for Generic Segmentation
Our main contribution is a new method for learning a pixel-wise representation that reflects segment relatedness.
Learning Discrete Weights Using the Local Reparameterization Trick
We show how a simple modification to the local reparameterization trick, previously used to train Gaussian distributed weights, enables the training of discrete weights.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
