Extensions: ECCV 2020 Workshop – Beyond mAP: Reassessing the Evaluation of Object Detectors + 3rd Probabilistic Object Detection (PrOD) Challenge

Call for Papers Extension:

ECCV 2020 Workshop – Beyond mAP: Reassessing the Evaluation of Object Detectors

3rd Probabilistic Object Detection (PrOD) Challenge

 

Workshop link

https://nikosuenderhauf.github.io/roboticvisionchallenges/eccv2020

 

We are pleased to announce an extension to the deadlines of both our ECCV 2020 workshop and associated Probabilistic Object Detection (PrOD) Challenge. Updated dates and workshop/challenge details below.

 

New Dates

  • Final Challenge Submission – 05 August 2020 Midnight UTC
  • Paper  Submission (workshop and challenge) – 07 August 2020 Midnight UTC
  • Paper + Competition Results  – 12 August 2020
  • Videos for Workshop Due – 20 August 2020
  • Workshop Interactive Sessions – 28 August 2020 UTC+1 (exact times TBC)

 

Workshop summary

This workshop assesses current evaluation procedures for object detection, highlights their shortcomings with respect to practical applications and opens discussion for possible improvements.

Through a focus on evaluation using challenges, the object detection community has been able to quickly identify which methods are effective by examining performance metrics. However, as this technological boom progresses, it is important to assess whether our evaluation metrics and procedures adequately align with how object detection will be used in practical applications such as robotics. Quantitative results should be easily reconciled with a detector’s performance in applied tasks. This workshop provides a forum to discuss these ideas and evaluate whether current standards meet the needs of the object detection community.

 

Call for Papers

We invite authors to contribute papers to the workshop. Topics of interest comprise, but are not limited to:

  • New evaluation measures/metrics for object detection
  • New evaluation/visualization tools to analyze object detection systems
  • New evaluation procedures for better understanding object detection performance
  • Examinations of current evaluation procedures
  • New datasets designed to examine specific challenges in object detection
  • New detection methods that provide contributions/insights unrewarded by current evaluation procedures (e.g. improved detector calibration, probabilistic object detection, etc.)

Author Instructions

  • Submissions must follow the ECCV format and be up to 4 pages in length including references
  • It is accepted if this is an abbreviated version of a larger paper published elsewhere if properly referenced
  • Submit your paper through CMT (link)
  • Accepted papers will provide a short video outlining their work which will be part of the ECCV online workshop system (details to come in the future so stay tuned to workshop website).

PrOD Competition

You may also be accepted to present your work at our conference if you perform well on the 3rd Probabilistic Object Detection (PrOD) Challenge.

 

This is a computer vision challenge designed to be more applicable for robotics applications where competitors must operate using video data, unusual viewing angles, and where you must estimate your spatial and semantic uncertainty.

 

Details can be found at the workshop website as well as the main competition page below.

 

(https://competitions.codalab.org/competitions/20597)

 

If you have any questions about the workshop or the challenge don't hesitate to get in contact.

 

Best regards,

 

Dr David Hall

 

Research Fellow

Robotic Vision Benchmarking and Evaluation Project

Australian Centre for Robotic Vision

Queensland University of Technology

 

e-mail: d20.hall@qut.edu.au

Phone: +61 7 31380656

ORCiD: 0000-0002-5520-0128

Website: https://sites.google.com/view/davidhallcv/home

International Workshop on Computational Aspects of Deep Learning (CADL), Milan, Italy, Jan 2021

********************************
ICPR 2020 Workshop on Computational Aspects of Deep Learning
Milan, Italy, January 10, 2021
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Organized in conjunction with ICPR 2020
=== SUBMISIONS ARE NOW OPEN!!! ====

CFP Special Issue on Computer Vision and Deep Learning for Remote Sensing Applications

 

===================================================================

CALL FOR PAPERS

 

* Special Issue on Computer Vision and Deep Learning for Remote Sensing Applications *

Journal: Remote Sensing (MDPI), IF 4.118

 

Guest Editors: Hyungtae Lee, Sungmin Eum, Claudio Piciarelli

 

Full info: http://mdpi.com/si/46402

 

Deadline: accepted papers will be published continuously (as soon as accepted) till the deadline (31 March 2021)

===================================================================

 

Abstract:

 

Today, the field of computer vision and deep learning is rapidly progressing into many applications, including remote sensing, due to its remarkable performance. Especially for remote sensing, a myriad of challenges due to difficult data acquisition and annotation have not been fully solved yet. The remote sensing community is waiting for a breakthrough to address these challenges by utilizing high-performance deep learning-based models that typically require large-scale annotated datasets.

 

This issue is looking for such breakthroughs focusing on the advances in remote sensing using computer vision, deep learning and artificial intelligence. Although broad in scope, contributions with a specific focus are expected.

 

For this special issue, we welcome the most recent advancements related, but not limited to:

 

* Deep learning architecture for remote sensing

* Machine learning for remote sensing

* Computer vision method for remote sensing

* Classification / Detection / Regression

* Unsupervised feature learning for remote sensing

* Domain adaptation and transfer learning with computer vision and deep learning for remote sensing

* Anomaly/novelty detection for remote sensing

* New dataset and task for remote sensing

* Remote sensing data analysis

* New remote sensing application

* Synthetic remote sensing data generation

* Real-time remote sensing

* Deep learning-based image registration

 

Dr. Hyungtae Lee

Dr. Sungmin Eum

Dr. Claudio Piciarelli

Guest Editors

ECCV 2020: call for academic research demos

We're pleased to invite academic and industrial researchers to submit
applications for virtual demonstrations during ECCV2020. Since the
conference has become virtual, so will the demos. Virtual demos will
consist of a pre-recorded demo video and a live Q&A session via video
chat. During the Q&A session you have the possibility to run live
demos too. This is a unique opportunity to showcase research results
and computer vision systems to the conference attendees.

All researchers in computer vision and related disciplines are invited
to submit an application to present demonstrations at ECCV 2020.

More information: https://eccv2020.eu/academic-demos/
Submission form: https://forms.gle/MReMsr2oQaBTra266
Submission deadline: Friday July 24

Contact: eccv20demos@eccv2020.eu

11th International Conference on Pattern Recognition Systems

ICPRS 2021 : 11th International Conference on Pattern Recognition Systems

Link: http://www.icprs.org

When Mar 15, 2021 – Mar 19, 2021
Where Virtual
Submission Deadline Sep 25, 2020
Notification Due Nov 27, 2020
Final Version Due Dec 28, 2020

The 11th International Conference on Pattern Recognition Systems (ICPRS-21) is an annual event that follows ICPRS-19, ICPRS-18, ICPRS-17 and ICPRS-16, a continuation of the successful Chilean Conference on Pattern Recognition that reached its 6th edition in 2014. In 2021 it is organised by the Universidad de Talca (Chile) and the Chilean Association for Pattern Recognition (ACHiRP, a member of the IAPR) and it is expected to be endorsed by the IAPR (tbc) and sponsored by the Vision and Imaging Professional Network of the Institution of Engineering and Technology (IET). As in previous years, papers will be published in electronic proceedings. Papers deemed to be of the required standard AND presented at the conference, will be normally indexed in IEEE Xplore and Scopus. All paper submissions need to be submitted via Conftool to be peer-reviewed by an international panel of experts. Excellent papers will be encouraged to submit extended versions for consideration in a JCR-indexed journal (tba). There will be a good set of keynote talks.

An innovative aspect of this conference is that it will be mainly virtual so that authors, invited speakers and delegates will be able to attend through a webinar system.

Another innovations is that there will be a special category of “Student Papers”, where the first author must be a student (undergraduate or postgraduate). There will be a special prize for best student paper.

All paper submissions will be submitted on-line to be peer-reviewed by an international panel of experts. Please note that all papers will be checked by a plagiarism detecting software so that papers that exceed a threshold of coincidence will not be passed on for reviews.

There will be delegate fee discounts for authors, students and members of the sponsoring organisations.

Prospective authors are invited to submit full papers papers describing novel and previously unpublished results on all aspects of Pattern Recognition Systems, from academia, industry, NGOs and others, to be selected for oral presentations or posters, on topics including, but not limited to:

  • Artificial Intelligence Techniques in Pattern Recognition
  • Bioinformatics Clustering
  • Biometrics (including face recognition)
  • Computer Vision
  • Data Mining and Big Data
  • Deep Learning and Neural Networks for Pattern Recognition
  • Document Processing and Recognition
  • Fuzzy and Hybrid Techniques in PR
  • High Performance Computing for Pattern Recognition
  • Image Processing and Analysis
  • Kernel Machines
  • Mathematical Morphology
  • Mathematical Theory of Pattern Recognition
  • Natural Language Processing and Recognition
  • Object Detection, Tracking and Recognition
  • Pattern Recognition Principles
  • Real Systems, Applications and Case Studies of Pattern Recognition (e.g. health, environment, weather prediction,natural disasters, transportation, etc.)
  • Robotics
  • Remote Sensing
  • Shape and Texture Analysis
  • Social Media and HCI
  • Signal Processing and Analysis
  • Statistical Pattern Recognition
  • Syntactical and Structural Pattern Recognition
  • Voice and Speech Recognition

                                
							
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