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

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.

To participate in the competition, and for more information around the data and submission format, please go to our Codalab page.

Important Dates

To be announced.

Invited Speakers


To be announced.


The Robotic Vision Challenges organisers are with the Australian Centre for Robotic Vision and Google AI.

Niko Sünderhauf
Queensland University of Technology
Feras Dayoub
Queensland University of Technology
Anelia Angelova
Google Brain
David Hall
Queensland University of Technology
John Skinner
Queensland University of Technology
Gustavo Carneiro
University of Adelaide