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[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
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[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
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Awesome Generative Adversarial Networks with tensorflow
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Research Framework for easy and efficient training of GANs based on Pytorch
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iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in…
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查看技能说明🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (ad…
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ICface: Interpretable and Controllable Face Reenactment Using GANs
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StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
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[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs
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Code for APDrawingGAN: Generating Artistic Portrait Drawings from Face Photos with Hierarchical GANs (CVPR 2019 Oral)
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Generative AI Image and Video Toolset with GANs and Diffusion for Real-World Applications
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All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
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PyTorch implementation of "Improved Techniques for Training Single-Image GANs" (WACV-21)
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PyTorch Implementation of DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs
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