[visionlist] [CFP] 3rd Workshop on Learning with Limited Labelled Data for Image and Video Understanding, CVPR24

menna seyam menna.seyam at gmail.com
Fri Jan 26 13:35:14 -04 2024

*3rd Workshop on* *Learning with Limited Labelled Data for Image and Video
Understanding, (L3D-IVU) *in conjunction with IEEE/CVF Conference on
Computer Vision and Pattern Recognition (CVPR), 2024.

*** FULL PAPER SUBMISSION DEADLINE: March 6th 2024 23:59 PST ***

Workshop Website: https://sites.google.com/view/l3divu2024/call-for-papers
CMT3 Submission: *https://cmt3.research.microsoft.com/L3DIVUCVPR2024/*


We encourage submissions that are under one of the topics of interest, but
also we welcome other interesting and relevant research for learning with
limited labelled data.


      Few-Shot classification, detection and segmentation in still images
      and video, including objects, actions, scenes and object tracking.

      Zero-shot learning in video understanding.

      Video and language modelling.

      Self supervised Learning in video related tasks.

      Weakly/Semi supervised learning in video understanding.

      Transfer Learning.

      Open-set learning.

      New benchmarks and metrics.

      Real-world applications discussing the societal impact of few-shot

Accepted papers will be presented at the poster session, some as orals and
there will be paper/s awarded best paper award.

*Submission Guidelines:*


   We accept submissions of *max 8 pages* (excluding references). We
   encourage authors to submit 4 page work as well.

   We accept dual submissions to *CVPR 2024* and *L3D-IVU 2024*.

   Submitted manuscripts should follow the CVPR 2024 paper template


   Submissions will be rejected without review if they:

      Contain more than 8 pages (excluding references).

      Violate the double-blind policy.

      Violate the dual-submission policy for papers with more than 4 pages
      excluding references.


   The accepted papers will be linked at the workshop webpage. It will also
   be in the main conference proceedings if the authors agree (this option is
   valid only for *full-length papers not published at CVPR 2024*)

   Papers will be peer reviewed under double-blind policy, and must be
   submitted online through the CMT submission system.

   Best regards,

   Mennatullah Siam, PhD

   Ontario Tech University, Canada.
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