[image 03623] [論文募集] ICCV 2019 MDALC Workshop (Zero-Shot, Few-Shot, Meta, Cross-Domain Learning)

[Nakamasa Inoue]

Image-mlの皆様,

東京工業大学の井上です。

ICCV 2019で下記のワークショップを開催致します。
様々なデータを対象とした、少量データでの学習やゼロショット学習を中心に、
幅広く論文を募集しておりますので、ご投稿をご検討頂けますと幸いです。

Multi-Discipline Approach for Learning Concepts - Zero-Shot, One-Shot, Few-Shot and Beyond
詳細: http://www.lsfsl.net/ws/
投稿締切: 2019年7月26日 (実際には延長する予定です)
開催日: 2019年10月27日 (ICCV2019併催のためSeoulでの開催です)

井上 中順

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**** Call for Papers: MDALC Workshop in conjunction with ICCV 2019 ****

The 1st Workshop on Multi-Discipline Approach for Learning Concepts - Zero-Shot, One-Shot, Few-Shot and Beyond
Website: http://www.lsfsl.net/ws/

==== IMPORTANT DATES ====
 Paper Submission: July 26th
 Notification: August 22nd
 Workshop: October 27th AM, 2019, Seoul, Korea

==== CALL FOR PAPERS ====
Recent studies on zero-shot, one-shot, and few-shot learning have shown the effectiveness of collaboration between computer vision and natural language processing. This workshop promotes deeper and wider collaboration across many research fields to scale-up these studies. We call papers of the following topics for learning concepts (objects, actions, scenes etc) from various types of data.
 * Few-/Low-/k-Shot Learning
 * One-Shot Learning
 * Zero-Shot Learning
 * Cross-Domain Learning
 * Meta Learning
 * Scope of data: Image, Video, Text, Audio, and Sensor Data
Details: http://www.lsfsl.net/ws/

We welcome two types of submissions:
 * Research Papers (4-8 pages excluding references, unpublished original research)
 * Extended Abstracts (2 pages including references, preliminary work or published work)
All submissions should be anonymized, formatted according to the template of ICCV 2019.
Submission Page: https://cmt3.research.microsoft.com/MDALC2019

==== INVITED SPEAKER ====
Cees G.M. Snoek
Professor, University of Amsterdam
http://www.ceessnoek.info/

==== ORGANIZERS ====
Nakamasa Inoue, Tokyo Institute of Technology
Hirokatsu Kataoka, AIST
Yoshitaka Ushiku, OMRON SINIC X Corporation
Yusuke Matsui, The University of Tokyo
Koichi Shinoda, Tokyo Institute of Technology
Shin'ichi Satoh, National Institute of Informatics
Benoit Huet, EURECOM
Chong-Wah Ngo, City University of Hong Kong