PhotographicImageSynthesiswithCascadedRefinementNetworks-Pytorch
Image synthesis library
An implementation of cascaded refinement networks for generating photorealistic images from semantic layouts
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
65 stars
2 watching
10 forks
Language: Python
last commit: about 7 years ago cityscapesdeep-learninghigh-resolutionneural-networkphotorealistic-based-renderingsemantic-segmentationvgg19
Related projects:
Repository | Description | Stars |
---|---|---|
| A PyTorch toolbox for supporting research and development of domain adaptation, generalization, and semi-supervised learning methods in computer vision. | 1,236 |
| A PyTorch project for comparing image classification models and facilitating quick experiment setup | 366 |
| A PyTorch implementation of an image-to-image translation model that generates new images from paired training data. | 1,491 |
| An implementation of semantic image synthesis via adversarial learning using PyTorch | 145 |
| An implementation of a deep learning model for generating images from text descriptions | 262 |
| Implementation of a deep learning model for generating high-quality images with improved stability and variation. | 538 |
| A PyTorch implementation of blending images by optimizing a Poisson loss with style and content loss | 435 |
| An implementation of a deep neural network architecture for image classification tasks | 273 |
| Provides a PyTorch implementation of several computer vision tasks including object detection, segmentation and parsing. | 1,191 |
| Provides a basic framework for training deep learning models on image classification tasks using PyTorch | 187 |
| Implementations of deep learning architectures using PyTorch for image classification tasks on various datasets. | 112 |
| Implementation of semantic segmentation models and datasets using PyTorch | 1,705 |
| A PyTorch implementation of V-Net for volumetric medical image segmentation | 703 |
| A PyTorch implementation of a deep learning-based method for generating interactive scenes with specified object attributes and relations | 188 |
| An implementation of an image-to-image translation algorithm using deep learning and PyTorch | 428 |