Self-Supervision & Contrastive Frameworks - A Vision-Based Review
Offered By: Stanford University via YouTube
Course Description
Overview
Syllabus
Intro
SS Learning: Invariant Representations
Pre-text Tasks: A Deeper Dive
Contrastive Learning: Entity Discrimination
Contrastive Learning: Problem
SimCLR: Simple Contrastive Learning Representatio
SimCLR: Architecture
SimCLR: Loss Function
SimCLR: Findings
MoCo V2: Momentum Contrast
MoCo V2: Architecture
MoCo V2: Main Principle
MoCoV2: Loss Function
MoCo V2: Findings
BYOL: Bootstrap Your Own Latent
BYOL: Architecture
BYOL: Main Principle
BYOL: Findings
SWAV: Swapping Assignments between Views
SWAV: Architecture
SWAV: Loss Function
SWAV: Main Principle
SWAV: Multi-crop
SWAV: Additional Findings
DINO: Self-Distillation with NO labels
DINO: Attention-Maps
VIT (Vision Transformer): Architecture
DINO: Architecture
DINO: Loss Function
DINO: Main Principle
DINO: Multi-crop
DINO: Additional Findings Compute
Taught by
Stanford MedAI
Tags
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Computational Photography
Georgia Institute of Technology via Coursera Einführung in Computer Vision
Technische Universität München (Technical University of Munich) via Coursera Introduction to Computer Vision
Georgia Institute of Technology via Udacity