Menu
Sign In Search Podcasts Charts People & Topics Add Podcast API Pricing
Podcast Image

Chai Time Data Science

Yuki Asano | Self-Supervision | Self-Labelling | Labelling Unlabelled videos from scratch w multi-modal self-supervision | CV | CTDS.Show #81

09 Jul 2020

Description

Video Link: https://youtu.be/LPdbnasJ9wI Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this episode, Sanyam Bhutani interviews Computer Vision Researcher at the Oxford VGG Group: Yuki Asano. They talk all about Yuki's journey into Computer Vision and his research interests, how Yuki approaches research. They also discuss three of Yuki's recent works and Yuki walks us through the process of how he approached the projects, along with an interesting overview of the same. Links: A critical analysis of self-supervision, or what we can learn from a single image: https://arxiv.org/abs/1904.13132 Self-labelling via simultaneous clustering and representation learning: https://arxiv.org/abs/1911.05371 Labelling unlabelled videos from scratch with multi-modal self-supervision: https://arxiv.org/abs/2006.13662 Follow: Yuki Asano: https://twitter.com/y_m_asano https://www.linkedin.com/in/yuki-m-asano/ https://yukimasano.github.io Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani. You can expect weekly episodes every available as Video, Podcast, and blogposts. If you'd like to support the podcast: https://www.patreon.com/chaitimedatascience Intro track: Flow by LiQWYD https://soundcloud.com/liqwyd

Audio
Featured in this Episode

No persons identified in this episode.

Transcription

This episode hasn't been transcribed yet

Help us prioritize this episode for transcription by upvoting it.

0 upvotes
🗳️ Sign in to Upvote

Popular episodes get transcribed faster

Comments

There are no comments yet.

Please log in to write the first comment.