YoVDO

DALI 2018 - Andreas Geiger: How to Satisfy the Thirst for Data

Offered By: Andreas Geiger via YouTube

Tags

Computer Vision Courses Data Analysis Courses Machine Learning Courses Mixed Reality Courses Generalization Courses Optical Flow Courses

Course Description

Overview

Explore cutting-edge approaches to addressing data scarcity in machine learning with Andreas Geiger's insightful conference talk. Delve into innovative techniques such as specialized architectures, soft constraints, self-supervision, mixed reality, and label transfer. Gain valuable insights on improving optical flow algorithms and enhancing generalization capabilities in data-hungry applications. Discover how these methods can revolutionize the field of computer vision and help overcome the challenges posed by limited labeled datasets.

Syllabus

Intro
The problem
Optical flow
Specialized architectures
Soft constraints
Self supervision
Mixed Reality
Label Transfer
Generalization


Taught by

Andreas Geiger

Related Courses

Social Network Analysis
University of Michigan via Coursera Intro to Algorithms
Udacity Data Analysis
Johns Hopkins University via Coursera Computing for Data Analysis
Johns Hopkins University via Coursera Health in Numbers: Quantitative Methods in Clinical & Public Health Research
Harvard University via edX