Multi-Discipline Approach for Learning Concepts - Zero-Shot One-Shot Few-Shot and Beyond



The 1st Workshop in Conjunction with ICCV 2019

From what data can we learn concepts such as objects, actions, and scenes? 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. With the common theme Learning Concepts we hope to provide a platform for researchers to exchange knowledge from their respective backgrounds.

Call for Papers

We call papers of the following 5x5 topics for learning concepts (objects, actions, scenes etc) from various types of data.

· Few-/Low-/k-Shot Learning from Image Data
· One-Shot LearningVideo Data
· Zero-Shot LearningText Data
· Cross-Domain LearningAudio Data
· Meta LearningSensor Data

This scope includes (but not limited to)

· Zero-Shot Learning for Object Detection from Images
· Few-Shot Learning for Action Recognition from Videos
· One-shot Learning for Scene Understanding from Images with Texts
· Meta Learning for Video Captioning
· Joint Image-Text Embeddings for Cross-Domain Learning
· Joint Audio-Visual Embeddings for k-Shot Classification
· One-Shot/Imitation Learning from Video Data with Sensory Inputs

and the other combinations of learning frameworks and tasks. The organizers will also provide a new challenging dataset, namely Few-Shot Verb Image Dataset with images of 1,500 verb concepts. This is a part of the Large-Scale Few-Shot Learning Challenge to create a large-scale platform for benchmarking few-shot, one-shot, and zero-shot learning algorithms. Papers using this dataset are also acceptable through the regular review process (This is optional).

Guide for Authors

We invite original research papers and extended abstracts. All submissions should be anonymized, formatted according to the template of ICCV 2019.
Research Papers (4-8 pages excluding references) should contain unpublished original research. They will be published in the ICCV workshop proceedings, and will be archived in the IEEE Xplore Digital Library and the CVF.
Extended Abstracts (2 pages including references) about preliminary work or published work will be archived on this website.
Please submit papers via the submission system (https://cmt3.research.microsoft.com/MDALC2019).

Important Dates and Venue

Research Paper Submission: August 2nd (11:59 PM, Pacific Time), 2019
Extended Abstract Submission: August 26th (11:59 PM, Pacific Time), 2019
Due to several requests, we have decided to extend the deadline for submission.
Workshop Paper Submission: July 26th, 2019
Notification: August 22nd (Research Papers), September 5th (Extended Abstracts)
Camera-ready: August 29th (Research Papers), September 12th (Extended Abstracts)
Workshop: October 27th AM at the same venue as ICCV 2019 in Seoul, Korea.

Invited Speakers

Cees G.M. Snoek
Professor, University of Amsterdam

Organizers

Nakamasa Inoue
Tokyo Tech
Hirokatsu Kataoka
AIST
Yoshitaka Ushiku
OSX
Yusuke Matsui
UTokyo

Koichi Shinoda
Tokyo Tech
Shin'ichi Satoh
NII
Benoit Huet
EURECOM
Chong-Wah Ngo
CityU


This workshop is supported by JST ACT-I (JPMJPR16U5).

Contact

concepts-ws@googlegroups.com