“Masked Autoencoders Are Scalable Vision Learners” paper explained by Ms. Coffee Bean. Say goodbye to contrastive learning and say hello (again) to autoencoders in #ComputerVision! Love the simple, yet elegant idea!
► Check out our sponsor: Weights & Biases 👉 https://wandb.me/ai-coffee-break
📺 Vision Transformer explained: https://youtube.com/playlist?list=PLpZBeKTZRGPMddKHcsJAOIghV8MwzwQV6
Thanks to our Patrons who support us in Tier 2, 3, 4: 🙏
donor, Dres. Trost GbR, Yannik Schneider
➡️ AI Coffee Break Merch! 🛍️ https://aicoffeebreak.creator-spring.com/
Paper 📜: He, Kaiming, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Doll'ar and Ross B. Girshick. “Masked Autoencoders Are Scalable Vision Learners.” (2021). https://arxiv.org/abs/2111.06377
References:
🔗 https://blog.keras.io/building-autoencoders-in-keras.html
🔗 https://www.deeplearningbook.org/
🔗 https://twitter.com/giffmana/status/1462446494766837773
📺 ViT video: https://youtu.be/DVoHvmww2lQ
📺 DeiT: https://youtu.be/-FbV2KgRM8A
📺 Swin Transformer: https://youtu.be/SndHALawoag
Outline:
00:00 Intro
00:41 Weights & Biases (Sponsor)
02:10 What are autoencoders?
05:03 Differences between vision and language masked autoencoding
07:02 How does masked autoencoding work for images?
▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀
🔥 Optionally, pay us a coffee to help with our Coffee Bean production! ☕
Patreon: https://www.patreon.com/AICoffeeBreak
Ko-fi: https://ko-fi.com/aicoffeebreak
▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀
----------------
🔗 Links:
AICoffeeBreakQuiz: https://www.youtube.com/c/AICoffeeBreak/community
Twitter: https://twitter.com/AICoffeeBreak
Reddit: https://www.reddit.com/r/AICoffeeBreak/
YouTube: https://www.youtube.com/AICoffeeBreak
#AICoffeeBreak #MsCoffeeBean #MachineLearning #AI #research