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Found 5 papers, 1 papers with code
ContrastCAD: Contrastive Learning-based Representation Learning for Computer-Aided Design Models
However, learning CAD models is still a challenge, because they can be represented as complex shapes with long construction sequences.
Brick partition problems in three dimensions
As a generalization of the above question, we also seek the minimum size $s(d, k)$ of a brick partition $\mathcal{P}_d$ of a $d$-dimensional brick where each axis-parallel plane intersects at least $k$ bricks in $\mathcal{P}_d$.
Combinatorics
Total Style Transfer with a Single Feed-Forward Network
To transfer the style of an arbitrary image to a content image, these methods used a feed-forward network with a lowest-scaled feature transformer or a cascade of the networks with a feature transformer of a corresponding scale.
Uncorrelated Feature Encoding for Faster Image Style Transfer
Although the pre-trained network is used to generate responses of receptive fields effective for representing style and content of image, it is not optimized for image style transfer but rather for image classification.
Unbiased Image Style Transfer
To solve this problem of the biased network, we propose an unbiased learning technique which uses unbiased training data and corresponding unbiased loss for alpha = 0. 0 to make the feed-forward networks to generate a zero-style image, i. e., content image when alpha = 0. 0.
