[robotics-worldwide] [meetings] ECCV2020 - Call for Participants: 3rd ACRV Probabilistic Object Detection (PrOD) Challenge

David Hall d20.hall at qut.edu.au
Wed Mar 4 09:18:53 PST 2020

Call for Participants: Australian Centre of Robotic Vision (ACRV) 3rd Probabilistic Object Detection (PrOD) Challenge.

The Australian Centre for Robotic Vision is pleased to announce the third iteration of their first robotic vision challenge on probabilistic object detection. In the probabilistic object detection (PrOD) challenge, participants have to detect objects in video data and provide accurate estimates of spatial and semantic uncertainty. High performing competitors in this iteration of the challenge will be invited to present their work at our ECCV 2020 Workshop Beyond mAP: Reasessing the Evaluation of Object Detectors<https://urldefense.com/v3/__https://nikosuenderhauf.github.io/roboticvisionchallenges/eccv2020__;!!LIr3w8kk_Xxm!7JUVMOOoe5TQWP-NHaZmDLPSf_yAAHOZkYx-WwHSm901CYacQCLQCkIKCWkQYoNUeFn3AyRM$ > and receive a monetary award.

To compete in the challenge and for the full challenge details, please see our competition website (https://urldefense.com/v3/__https://competitions.codalab.org/competitions/20597__;!!LIr3w8kk_Xxm!7JUVMOOoe5TQWP-NHaZmDLPSf_yAAHOZkYx-WwHSm901CYacQCLQCkIKCWkQYoNUeGEDnHYJ$ )

Important Dates


  *   Final Detection Submissions Due - 14th July 2020 Midnight UTC
  *   Final Paper Submissions Due - 21st July 2020 Midnight UTC
  *   Winner Announcements and Workshop Invitations Sent - 28th July 2020
  *   Challenge ECCV Workshop - 28th August 2020



To promote object detection systems that can be treated as any other sensor in a robotic system which can be trusted within the established framework of Bayesian information fusion, our challenge encourages development of probabilistic object detection systems that provide meaningful estimates of both spatial and semantic uncertainty.

In contrast to traditional object detection challenges (such as COCO), our challenge evaluates detections using the new probability-based detection quality (PDQ) measure which rewards accurate uncertainty estimates, and penalises both overconfident and underconfident detections.

Within the challenge, competitors will detect 30 classes of object in over 56,000 images from 18 high-fidelity simulated video sequences spanning 3 unique environments viewed at 3 different simulated robot heights with both day and night lighting conditions.

As well as the ECCV 2020 PrOD challenge, we have a continuous evaluation server available for those who want to develop work in this field of research.

We invite anyone who is interested in object detection and appreciates a good challenge to please participate and compete in the competition so that we may continue to push the state-of-the-art in object detection in directions more suited to robotics applications.

ECCV 2020 PrOD Competition: https://urldefense.com/v3/__https://competitions.codalab.org/competitions/20597__;!!LIr3w8kk_Xxm!7JUVMOOoe5TQWP-NHaZmDLPSf_yAAHOZkYx-WwHSm901CYacQCLQCkIKCWkQYoNUeGEDnHYJ$ 

Continuous PrOD Challenge: https://urldefense.com/v3/__https://competitions.codalab.org/competitions/20595__;!!LIr3w8kk_Xxm!7JUVMOOoe5TQWP-NHaZmDLPSf_yAAHOZkYx-WwHSm901CYacQCLQCkIKCWkQYoNUeC1Ry9LW$ 

Contact Details


E-mail: contact at roboticvisionchallenge.org<mailto:contact at roboticvisionchallenge.org>

Twitter: @RobVisChallenge

Website: roboticvisionchallenge.org

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