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Found 6 papers, 3 papers with code
Physically-admissible polarimetric data augmentation for road-scene analysis
Polarimetric imaging, along with deep learning, has shown improved performances on different tasks including scene analysis.
Pixel-wise Conditioned Generative Adversarial Networks for Image Synthesis and Completion
We investigate the influence of this regularization term on the quality of the generated images and the fulfillment of the given pixel constraints.
Pixel-wise Conditioning of Generative Adversarial Networks
In this paper, we study the effectiveness of conditioning GANs by adding an explicit regularization term to enforce pixel-wise conditions when very few pixel values are provided.
Dilated Spatial Generative Adversarial Networks for Ergodic Image Generation
In combination with convolutional (for the discriminator) and de-convolutional (for the generator) layers, they are particularly suitable for image generation, especially of natural scenes.
CTCModel: a Keras Model for Connectionist Temporal Classification
We report an extension of a Keras Model, called CTCModel, to perform the Connectionist Temporal Classification (CTC) in a transparent way.
Gradient-based deterministic inversion of geophysical data with Generative Adversarial Networks: is it feasible?
Global probabilistic inversion within the latent space learned by Generative Adversarial Networks (GAN) has been recently demonstrated (Laloy et al., 2018).
Geophysics
