Swin Transformer paper animated and explained

Swin Transformer paper animated and explained

Nov 06, 2021
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Swin Transformer paper explained, visualized, and animated by Ms. Coffee Bean. Find out what the Swin Transformer proposes to do better than the ViT vision transformer. πŸ“Ί ViT explained: https://youtu.be/DVoHvmww2lQ πŸ“Ί Transformer explained: https://youtu.be/FWFA4DGuzSc πŸ“Ίβ–Ί Positional embeddings (playlist): https://youtube.com/playlist?list=PLpZBeKTZRGPOQtbCIES_0hAvwukcs-y-x β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€ Thanks to our Patrons who support us in Tier 2, 3, 4: πŸ™ donor, Dres. Trost GbR, Yannik Schneider πŸ”₯ Optionally, pay us a coffee to help with our Coffee Bean production! β˜• Patreon: https://www.patreon.com/AICoffeeBreak Ko-fi: https://ko-fi.com/aicoffeebreak β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€β–€ Paper discussed: πŸ“œ Liu, Ze, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo. "Swin transformer: Hierarchical vision transformer using shifted windows." arXiv preprint arXiv:2103.14030 (2021). https://arxiv.org/abs/2103.14030 πŸ’» Swin Transformer code on GitHub: https://github.com/microsoft/Swin-Transformer Outline: 00:00 Problems with ViT / Swin Motivation 04:16 Swin Transformer explained 06:00 Shifted Window based Self-attention 08:58 positional embeddings in the Swin Transformer 09:29 Task performance of the Swin Transformer Music 🎡 : Bay Street Millionaires by Squadda B --------------------- πŸ”— 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​ Video and thumbnail contain emojis designed by OpenMoji – the open-source emoji and icon project. License: CC BY-SA 4.0 16x16 pixels comprehensible artificial intelligence

00:00 Problems with ViT / Swin Motivation 04:16 Swin Transformer explained 06:00 Shifted Window based Self-attention 08:58 positional embeddings in the Swin Transformer 09:29 Task performance of the Swin Transformer
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