[CFP] Continual Learning Challenge @ CVPR 2020 is Open!

Dear all,

We are excited to announce the opening of the challenge on " Continual Learning for Computer Vision " in the context of the CLVision workshop at CVPR 2020 !

3 different tracks , more than 2,300$ in prizes and a starting repository with all the necessary to start without any effort!

You are all invited to partecipate!

Important Links

Important Dates

  • Beginning of the pre-selection phase (release of data and baselines): 15th Feb 2020
  • Scoreboard opening for submissions: 27th Feb 2020
  • Pre-selection phase ends: 1st May 2020
  • Paper submission starts: 2st May 2020
  • Paper submission ends: 8st May 2020
  • Final evaluation starts: 9st May 2020
  • Final ranking is published: 20th May 2019

CLVision Workshop Organizers

  • Pau Rodriguez, Element AI.
  • German Parisi, University of Hamburg.
  • David Vazquez, Element AI.
  • Vincenzo Lomonaco, University of Bologna.
  • Nikhil Churamani, University of Cambridge.
  • Zhiyuan (Brett) Chen, Google.
  • Marc Pickett, Google Research.

Challenge Chairs

  • Giulia Pasquale, Istituto Italiano di Tecnologia
  • Qi (Roger) She, Intel Labs
  • Issam Laradji, University of British Columbia
  • Massimo Caccia, University of Montreal
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Still more than one month to go for the Continual Learning Challenge @ CVPR2020! :muscle:

With our starting repository you can submit your first solution in a matter of minutes, join the competition now! :point_down:

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More than 50 teams have decided to join the event and we are excited to see how their solutions will perform in this complex 3-tracks competition! You can still join till the end on March if you haven’t already!

Next deadlines:

  • Pre-selection phase ends: 1st May 2020
  • Short Paper submission starts: 2st May 2020
  • Short Paper submission ends: 8st May 2020
  • Final evaluation starts: 9st May 2020
  • Final ranking will be published: 20th May 2019

Participants should submit a dockerized solution before the 10th of May anywhere on earth (we updated the basic repo with some initial instructions).

May the best win!