세미나안내

세미나안내

Toward Annotation Efficient Learning for Computer Vision

2020-12-08
  • 2,200
오태현 교수(POSTECH) / 2020.12.02

Biography

연도(부터까지)

기관명 직위(직명)

2020

POSTECH 전자전기공학과 조교수

2019

2020 Facebook AI Research 방문연구원
2017 2019 MIT CSAIL

박사후연구원

2010 2017 KAIST

석사/박사

2006 2010 광운대학교

학사

 

Abstract

Recent progress in machine learning has led to many advances in engineering and science fields, including computer vision and graphics. Most notable successes have seen in supervised learning with deep neural networks. Despite these successes, as a consequence of using the high capacity models, we are struggling with a lack of high-quality annotations in supervised methods. Obtaining a massive amount of carefully annotated and curated data is often expensive or even challenging.

In this talk, I will present a few potential strategies for case-study, including self-/semi-supervised learning, generating synthetic data, injeting a prior to an architecture, borrowing different domain data, etc.

 

ZOOM : https://zoom.us/j/8978217407?pwd=d1pOZmF1OWlseEdZRVBpV3VuSkl3dz09

ID : 897 821 7407

PW : 1nTQDY

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