DALL-E: Zero-Shot Text-to-Image Generation | Paper Explained

Описание к видео DALL-E: Zero-Shot Text-to-Image Generation | Paper Explained

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In this video I cover DALL-E or "Zero-Shot Text-to-Image Generation" paper by OpenAI team.

They train a VQ-VAE to learn compressed image representations and then they train an autoregressive transformer on top of that discrete latent space and BPEd text.

The model learns to combine distinct concepts in a plausible way, image to image capabilities emerge, etc.

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✅ Paper: https://arxiv.org/abs/2102.12092

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⌚️ Timetable:

00:00 What is DALL-E?
03:25 VQ-VAE blur problems
05:15 transformers, transformers, transformers!
07:10 Stage 1 and Stage 2 explained
07:30 Stage 1 VQ-VAE recap
10:00 Stage 2 autoregressive transformer
10:45 Some notes on ELBO
13:05 VQ-VAE modifications
17:20 Stage 2 in-depth
23:00 Results
24:25 Engineering, engineering, engineering
25:40 Automatic filtering via CLIP
27:40 More results
32:00 Additional image to image translation examples

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