A resource for learning about Machine learning & Deep Learning
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Updated
Jul 12, 2024 - Python
A resource for learning about Machine learning & Deep Learning
PyTorch 官方中文教程包含 60 分钟快速入门教程,强化教程,计算机视觉,自然语言处理,生成对抗网络,强化学习。欢迎 Star,Fork!
A modern PyTorch implementation of SRGAN
[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL
Implement Human Pose Transfer papers with Pytorch
PyTorch implementation of Deterministic Generative Adversarial Imitation Learning (GAIL) for Off Policy learning
Noise2Void - Learning Denoising from Single Noisy Images
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Person re-identification, a tool used in intelligent video surveillance, is the task of correctly identifying individuals across multiple images captured under varied scenarios from multiple cameras. Solving this problem is inherently a challenging one because of the issues posed to it by low resolution images, illumination changes per image, un…
Pytorch implementation of a Conditional WGAN with Gradient Penalty
Non-official + minimal reimplementation of HoloGAN by Nguyen-Phuoc, et al: https://arxiv.org/abs/1904.01326
Image-to-Image Translation with Conditional Adversarial Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
PANDA (Pytorch) pipeline, is a computational toolbox (MATLAB + pytorch) for generating PET navigators using Generative Adversarial networks.
Enhanced Super-Resolution Generative Adversarial Networks
Noise2Noise: Learning Image Restoration without Clean Data
[CNN PROGRAMMING] 005 - DCGAN
Spectral Normalization for Generative Adversarial Networks
Pytorch implementation of BigGAN Generator with pretrained weights
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