Sep 7, 2021 · The non-local information e.g. long-range dependencies can reflect the relationship between image regions and complement the neural network.
Sep 14, 2021 · In this paper, we propose a Graph Convolutional Architecture (GCA) for GANs to tackle this problem. GCA constructs a pixel-level graph structure ...
In this paper, we propose a Graph Convolutional Architecture (GCA) for GANs to tackle this problem. GCA constructs a pixel-level graph structure between image ...
In this paper, we propose a Graph Convolutional Architecture (GCA) for GANs to tackle this problem. GCA constructs a pixel-level graph structure between image ...
May 29, 2023 · Note that the feature vectors are extracted through a non-local and non-linear mapping using a convolutional network, specifically designed for ...
Unlike other models, NL-CycleGAN leverages non-local features to capture long-term interdependence, which is crucial for accurately assessing core qualities.
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Spider GANs lever- age underlying similarity, not necessarily visual, between datasets to improve generator learning. Similar discrepancies between visual ...
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Aug 25, 2024 · Even when trained on only 4 classes of ProGAN, GFF achieves nearly 99% accuracy on unseen GANs and maintains an impressive 97% accuracy on ...
We enhance the conventional physics-informed neural network framework by implementing the principles of data-driven computational mechanics into GANs.
To facilitate this, we leverage existing GAN models pretrained on large-scale datasets (like ImageNet) to intro- duce additional knowledge (which may not exist.
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