CVPR 21 Workshop on CV4Animals

Call for Paper
CVPR 2021 Workshop on CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling 
Submission deadline11:59 pm, Apri 30, 2021 (Pacific Time)
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Abstract
Many biological organisms have evolved to exhibit diverse behaviors, and understanding these behaviors is a fundamental goal of multiple disciplines including neuroscience, biology, animal husbandry, ecology, and animal conservation. These analyses require objective, repeatable, and scalable measurements of animal behaviors that are not possible with existing methodologies that leverage manual encoding from animal experts and specialists. Computer vision is having an impact across multiple disciplines by providing new tools for the detection, tracking, and analysis of animal behavior. This workshop brings together experts across fields to stimulate this new field of computer-vision-based animal behavioral understanding.

We solicit exciting non-archival papers on the related topics of CV4Animals. The selected papers will be presented in the workshop as a poster (will not be published in proceedings). There are two tracks.

Track 1 (unpublished work): Paper must follow the CVPR format, and be limited to 4 pages plus references. Papers will be reviewed in accordance with double blind policy, based on relevance, significance, and novelty.

Track 2 (published work): We look for papers already published at a peer-reviewed venue. Full paper can be submitted without a modification.


Our goal is to increase visibility and unique problems that arise when using computer vision to understand animal behavior. We welcome any papers around topics of:

– Animal Re-identification

– 3D Animal Reconstruction

– Animal Tracking and Modeling

– Animal Behavioral Analysis

– Animal Datasets

– CV Applications in Neuroscience, Biology, Animal Husbandry, Ecology, and Animal Conservation


Submission deadline11:59 pm, Apri 30, 2021 (Pacific Time)

Notification of selectionMay 21, 2021

Submission: CMT link (Track 1) and Google form (Track 2)

Live e-Lecture by Prof. LP Morency: ‘Multimodal AI: Understanding Human Behaviors’, 6th April 2021 17:00-18:00 CET. Upcoming AIDA AI excellence lectures

Dear AI scientist/engineer/student/enthusiast,

 

Prof. LP Morency (Carnegie Mellon University, Pittsburgh), a prominent AI researcher internationally, will deliver the e-lecture:

Multimodal AI: Understanding Human Behaviors’, on Tuesday 6th April 2021 17:00-18:00 CET (8:00-9:00 am PST), (12:00 am-1:00am CST),

see details in: http://www.i-aida.org/ai-lectures/

You can join for free using the zoom link: https://authgr.zoom.us/j/94136791572

 

The International AI Doctoral Academy (AIDA), a joint initiative of the European R&D projects AI4Media, ELISE, Humane AI Net, TAILOR, VISION, currently in the process of formation,

is very pleased to offer you top quality scientific lectures on several current hot AI topics, starting with the above mentioned e-lecture.

 

Lectures will be offered alternatingly by:

Top highly-cited senior AI scientists internationally or

Young AI scientists with promise of excellence (AI sprint lectures)

 

Lectures will be typically held once per week, Tuesdays 17:00-18:00 CET (8:00-9:00 am PST), (12:00 am-1:00am CST).  Attendance is free.

 

Other upcoming lectures:

1. Prof. Anibal Ollero (University of Seville, Spain), 4th May 2021 17:00 – 18:00 CET.

2. Prof. John Shawe-Taylor (University College London, UK), 18th May 2021 17:00 – 18:00 CET.

More lecture infos in: http://www.i-aida.org/future-lectures/

 

These lectures are disseminated through multiple channels and email lists (we apologize if you received it through various channels).

If you want to stay informed on future lectures, you can register in the email lists AIDA email list and CVML email list.

 

Best regards

Profs. M. Chetouani, P. Flach, B. O’Sullivan, I. Pitas, N. Sebe

WESTERN DIGITAL | Video Vigilancia

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CallParticipation: ImageCLEF Social Media User Data Awareness Task

ImageCLEFaware
*** CALL FOR PARTICIPATION ***
Images constitute a large part of the content shared on social
networks. Their disclosure is often related to a particular context
and users are often unaware of the fact that, depending on their
privacy status, images can be accessible to third parties and be used
for purposes which were initially unforeseen. For instance, it is
common practice for employers to search information about their future
employees, online.
Most existing approaches which propose feedback about shared data
focus on inferring user characteristics, and their practical utility
is rather limited. We hypothesize that user feedback would be more
efficient if conveyed through the real-life effects of data sharing.
The objective of the task is to automatically score user photographic
profiles in a series of situations with strong impact on her/his life.
*** TASK ***
Given a set of social media user profiles, participants will propose
machine learning techniques which provide a ranking of these in
various (unaware) usage situations.
*** DATA SET ***
A data set of 500 user profiles with 100 photos per profile was
created and annotated with an appeal score for a series of real-life
situations via crowdsourcing. User profiles are created by repurposing
a subset of the YFCC100M dataset. In accordance with GDPR, data
minimization is applied, and participants receive only the information
necessary to carry out the task in an anonymized form. Resources
include: (i) anonymized visual concept ratings for each situation
modeled; (ii) automatically extracted predictions for the images that
compose the profiles.
*** METRICS ***
The correlation with the ground truth will be measured using Pearson's
correlation coefficient. The final score of each participating team
will be obtained by averaging correlations obtained for individual
situations.
*** IMPORTANT DATES ***
– Task registration opens: November 16, 2020
– Development data release: February 15, 2021
– Test data release: March 15, 2021
– Run submission: May 10, 2021
– Working notes submission: May 28, 2021
– CLEF 2021 conference: September 21-24, Bucharest, Romania
*** REGISTER ***
*** OVERALL COORDINATION ***
Adrian Popescu, CEA LIST, France
Jérôme Deshayes-Chossart, CEA LIST, France
Bogdan Ionescu, University Politehnica of Bucharest, Romania
On behalf of the Organizers,
Adrian Popescu

Special Issue “Artificial Intelligence for Biomedical Sensing, Analysis and Treatment”

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We invite authors to submit high-quality papers whose topics include, but are not limited to, the following categories:

Medical image analysis
Healthcare informatics
Digital pathology
Biological cell analysis
Computational medicine
Drug discovery
Biomarker discovery
Disease fingerprints
Computational genetics
AI/Machine learning in medicine, medically oriented human biology, and healthcare
AI-based modeling and management of healthcare pathways and clinical guidelines
AI-based clinical decision making
AI in medical and healthcare education
Natural language processing in medicine and healthcare
Knowledge-based and agent-based systems
Automated reasoning and meta-reasoning in medicine.
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