DCGAN Tutorial with PyTorch Implementation

ExplainingAI · Beginner ·🧬 Deep Learning ·2y ago

Skills: Generative Models53%

About this lesson

In this video I cover DCGAN with the goal of understanding and implementing DCGAN from scratch in pytorch. We will be doing a dive deep into its architecture which will guide us on how to build a dcgan model. We will then implement dcgan from scratch and understand how the entire code for dcgan looks like and the different layers involved. We train dcgan for image generation on mnist dataset. We also train on celeb faces dataset to generate human faces with dcgan. We then get into visualizing the latent space of the face dcgan model and mnist model. Paper - http://tinyurl.com/exai-dcgan-paper Github Implementation - http://tinyurl.com/exai-dcgan-implementation Implementation Collaborator: Akansh Maurya https://akansh12.github.io/ https://www.linkedin.com/in/akansh-maurya/ 🔔 Subscribe : https://tinyurl.com/exai-channel-link 📌 Keywords: #generativeadversarialnetworks #DCGAN ⏱️ Timestamps 00:00 Intro 00:40 Recap of Generative Adversarial Networks 03:03 Architecture of DCGAN 05:05 Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks 05:52 DCGAN PyTorch Implementation 09:16 Code for DCGAN Training 10:49 DCGAN Image Generation on MNIST 11:21 Face DCGAN Results 11:30 Visualizing Latent Space of DCGAN 13:40 Arithmetic operation in Latent space of DCGAN 15:47 Gan Inversion 19:11 Manipulating image attributes using latent space 22:25 Thank You

Original Description

In this video I cover DCGAN with the goal of understanding and implementing DCGAN from scratch in pytorch. We will be doing a dive deep into its architecture which will guide us on how to build a dcgan model. We will then implement dcgan from scratch and understand how the entire code for dcgan looks like and the different layers involved. We train dcgan for image generation on mnist dataset. We also train on celeb faces dataset to generate human faces with dcgan. We then get into visualizing the latent space of the face dcgan model and mnist model. Paper - http://tinyurl.com/exai-dcgan-paper Github Implementation - http://tinyurl.com/exai-dcgan-implementation Implementation Collaborator: Akansh Maurya https://akansh12.github.io/ https://www.linkedin.com/in/akansh-maurya/ 🔔 Subscribe : https://tinyurl.com/exai-channel-link 📌 Keywords: #generativeadversarialnetworks #DCGAN ⏱️ Timestamps 00:00 Intro 00:40 Recap of Generative Adversarial Networks 03:03 Architecture of DCGAN 05:05 Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks 05:52 DCGAN PyTorch Implementation 09:16 Code for DCGAN Training 10:49 DCGAN Image Generation on MNIST 11:21 Face DCGAN Results 11:30 Visualizing Latent Space of DCGAN 13:40 Arithmetic operation in Latent space of DCGAN 15:47 Gan Inversion 19:11 Manipulating image attributes using latent space 22:25 Thank You

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Chapters (13)

Intro

0:40 Recap of Generative Adversarial Networks

3:03 Architecture of DCGAN

5:05 Unsupervised Representation Learning with Deep Convolutional Generative Adversar

5:52 DCGAN PyTorch Implementation

9:16 Code for DCGAN Training

10:49 DCGAN Image Generation on MNIST

11:21 Face DCGAN Results

11:30 Visualizing Latent Space of DCGAN

13:40 Arithmetic operation in Latent space of DCGAN

15:47 Gan Inversion

19:11 Manipulating image attributes using latent space

22:25 Thank You

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