This workshop will bring together the participants of the first Robotic Vision Challenge, a new competition targeting both the computer vision and robotics communities.
The new challenge focuses on probabilistic object detection. The novelty is the probabilistic aspect for detection: A new metric evaluates both the spatial and semantic uncertainty of the object detector and segmentation system. Providing reliable uncertainty information is essential for robotics applications where actions triggered by erroneous but high-confidence perception can lead to catastrophic results.
Participate in the Competition
To participate in the competition, and for more information around the data and submission format, please go to our Codalab page.
Our first challenge requires participants to detect objects in video data (from high-fidelity simulation). As a novelty, our evaluation metric rewards accurate estimates of spatial and semantic uncertainty using probabilistic bounding boxes. We developed a new probability-based detection quality (PDQ) evaluation measure for this challenge, please see the arxiv paper for more details.
Submissions must be accompanied by a 3-6 page paper explaining the method and external data used. Please use the CVPR paper format (no need to keep it double-blind) and upload your paper through our submission page on (CMT). Top performing submissions from the challenge will be invited to present their methods at the workshop. A total of $5000 AUD prize money will be rewarded to the competitors, subject to the rules explained on the Codalab page.
- 10 May 2019 Final Submissions to the Evaluation Server via Codalab
- 12 May 2019 Paper Submission via CMT
- 16 May 2019 Winner Announcements and Workshop Invitations
- 17 June 2019 Workshop at CVPR
- Jana Kosecka (George Mason University)
- Andreas Geiger (University of Tübingen)
- Ingmar Posner (University of Oxford)
To be announced.
The Robotic Vision Challenges organisers are with the Australian Centre for Robotic Vision and Google AI.