Ha0Tang/SelectionGAN
Multi-channel attention selection GAN for guided cross-view image-to-image translation published at CVPR 2019 and TPAMI.
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This repository implements SelectionGAN, a generative adversarial network with cascaded semantic guidance for cross-view image translation. The model uses multi-channel attention selection mechanisms to translate images across different views or semantic mappings. It builds on standard deep learning practices using PyTorch, with published results demonstrating image generation capabilities across multiple datasets including CVUSA and Dayton.
Frequently asked
- What is Ha0Tang/SelectionGAN?
- Multi-channel attention selection GAN for guided cross-view image-to-image translation published at CVPR 2019 and TPAMI.
- Is SelectionGAN open source?
- Yes — Ha0Tang/SelectionGAN is an open-source project tracked on heatdrop.
- What language is SelectionGAN written in?
- Ha0Tang/SelectionGAN is primarily written in Python.
- How popular is SelectionGAN?
- Ha0Tang/SelectionGAN has 466 stars on GitHub.
- Where can I find SelectionGAN?
- Ha0Tang/SelectionGAN is on GitHub at https://github.com/Ha0Tang/SelectionGAN.