Continual Semi-Supervised Learning @ IJCAI 2021 – Call for participation

July 28th, 2021 Daniela Lopez de Luise
We warmly invite all machine learning researchers to participate in the upcoming IJCAI 2021 First International Workshop on Continual Semi-Supervised Learning

https://sites.google.com/view/sscl-workshop-ijcai-2021/

The aim of this workshop is to formalise this new continual semi-supervised learning paradigm, and to introduce it to the machine learning community in order to mobilise effort in this direction. We present the first two benchmark datasets for this problem, derived from significant computer vision scenarios, and propose the first Continual Semi-Supervised Learning Challenges to the research community.

To attend, please follow IJCAI guidelines for workshop registration (early bird $80):
https://ijcai-21.org/registration-information/

Format —————————————————————————————————————–
The workshop is a full-day event, scheduled in two halves (see below) taking place on Thursday 19th August and Friday 20th August.
The event will be hosted on Gather Town, and will also be recorded via Zoom.
The programme is a blend of invited talks, oral presentations from the two award-winning papers, two poster sessions and a panel on the future of continual learning.

 

August 19 – 14:00 – 18:00 UTC

14:00

Opening remarks

 

 

 

14:10-15:10

 

 

 

Presentation of the benchmarks and challenges

 

15:10-15:40

 

Invited talk #1 – Razvan Pascanu

 

15:40-16:10

 

Invited talk #2 – Bing Liu

 

16:10-16:30

 

Coffee break

 

 

 

16:30-17:30

 

 

 

Poster session 1

 

17:30:18:00

 

Best student paper award oral presentation

 

August 20 – 14:00 – 18:00 UTC

 

14:00-14:30

 

Best paper oral presentation

 

 

 

14:30-15:30

 

 

 

Poster session 2

 

15:30-15:50

 

Coffee break

 

15:50-16:20

 

Invited talk #3 – Tinne Tuytelaars

 

16:20-16:50

 

Invited talk #4 – Chelsea Finn

 

 

 

16:50-17:50

 

 

 

Panel on future of continual learning

 

17:50-18:00

 

Award ceremony and closing remarks

Challenges ————————————————————————————————————

With this workshop we intend to propose to the community both a continual activity recognition (CAR) challenge and a continual crowd counting (CCC) challenge.

https://sites.google.com/view/sscl-workshop-ijcai-2021/challenges

based on a newly released Continual Activity Recognition (CAR) dataset, derived from a fraction of the MEVA (Multiview Extended Video with Activities) activity detection dataset (https://mevadata.org/), and a Continual Crowd Counting (CCC) dataset, derived from sequences from the Mall, UCSD and  FDST datasets.
Invited speakers —————————————————————————————————–
Razvan Pascanu (Deepmind)
Tinne Tuytelaars (KU Leuven)
Chelsea Finn (Stanford)
Bing Liu (University of Illinois at Chicago)

Accepted Papers —————————————————————————————————-


Lucas Caccia and Joelle Pineau  

SPeCiaL: Self-Supervised Pretraining for Continual Learning
(Best Paper Award)

Dhanajit Brahma, Vinay Kumar Verma and Piyush Rai
Hypernetworks for Continual Semi-Supervised Learning  

(Best Student Paper Award)

Jiangpeng He and Fengqing Zhu 
Unsupervised Continual Learning Via Pseudo Labels

Luca Monorchio, Marco Capotondi, Mario Corsanici, Wilson Villa, Alessandro De Luca and Francesco Puja 
Transfer and Continual Supervised Learning for Robotic Grasping through Grasping Features
Mahardhika Pratama, Andri Ashfahani and Edwin Lughofer 
Unsupervised Continual Learning via Self-Adaptive Deep Clustering Approach
Enrico Meloni, Alessandro Betti, Lapo Faggi, Simone Marullo, Matteo Tiezzi and Stefano Melacci 
Evaluating Continual Learning Algorithms by Generating 3D Virtual Environments
Qihan Yang, Fan Feng and Rosa H.M. Chan 
A Benchmark and Empirical Analysis for Replay Methods in Continual Learning
Andrea Rosasco, Antonio Carta, Andrea Cossu, Vicenzo Lomonaco and Davide Bacciu 
Distilled Replay: Overcoming Forgetting through Synthetic Samples
Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan and Yu Cao 
Self-supervised Novelty Detection for Continual Learning: A Gradient-based Approach Boosted by Binary Classification
Hermann Blum, Francesco Milano, René Zurbrügg, Roland Siegwart, Cesar Cadena and Abel Gawel 
Self-Improving Semantic Perception for Indoor Localisation
Sungmin Cha, Beomyoung Kim, Youngjoon Yoo and Taesup Moon 
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning

Ajmal Shahbaz, Salman Khan, Mohamad Asiful Hossain, Vincenzo Lomonaco, Kevin Cannons, Zhan Xu and Fabio Cuzzolin

International Workshop on Continual Semi-Supervised Learning: Introduction, Benchmarks and Baselines

 

Organising committee ———————————————————————————————-

Fabio Cuzzolin (Oxford Brookes University)
Kevin Cannons (Huawei Technologies Canada)
Vincenzo Lomonaco (University of Pisa and ContinualAI)
Irina Rish (University of Montreal and MILA)
Salman Khan (Oxford Brookes University)
Mohamad Asiful Hossain (Huawei Technologies Canada)
Ajmal Shahbaz (Oxford Brookes University)

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