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Vision-Language Models Explained
STOP Using Vision Language Models Until You Watch This #VisionLanguageModels #AIResearch #ComputerVision #TransformerModels
Vision-Language Models (VLMs) like CLIP, ALIGN, FLAVA, COCA are transforming how AI understands images and text together. In this 2–3 hour YouTube Live Masterclass, we’ll explore:

🔹 Introduction to VLMs — why they matter, and how they evolved from deep learning.
🔹 Background & Paradigm Development — from handcrafted features to Transformers.
🔹 Foundations of VLMs — CNNs, Vision Transformers, objectives (contrastive, generative, alignment).
🔹 Datasets — billion-scale image-text pairs (e.g., LAION, COCO, ImageNet).
🔹 VLM Pre-training Methods — CLIP, ALIGN, DeCLIP, FILIP, COCA, FLAVA, GLIP.
🔹 Transfer Learning — prompt tuning, adapters, fine-tuning tricks.
🔹 Knowledge Distillation — making VLMs smaller, faster, and task-specific.
🔹 Performance & Benchmarking — scaling laws, challenges, limitations.
🔹 Future Directions — multilingual models, 3D reasoning, efficiency, ethics.

👉 Paper Discussed: Vision-Language Models for Vision Tasks: A Survey
👉 Authors: Jingyi Zhang , Graduate Student Member, IEEE, Jiaxing Huang , 👉 Graduate Student Member, IEEE, Sheng Jin , and Shijian Lu
👉 Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 46, Issue: 8, August 2024)
👉 Page(s): 5625 - 5644
👉 Date of Publication: 26 February 2024
👉 PubMed ID: 38408000
👉 DOI: 10.1109/TPAMI.2024.3369699
👉 Link: https://ieeexplore.ieee.org/document/...
👉 Publisher: IEEE
👉You tube video link:    • STOP Using Vision Language Models Until Yo...  

📌 Stay tuned until the end for Q&A + Future Research Roadmap.

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