The CVPR2023 Embodied AI Workshop of our Robotic Vision Scene Understanding Challenge evaluates how well a robotic vision system can understand the semantic and geometric aspects of environments. The challenge is performed in simulation and consists of two distinct tasks: Object-based Semantic SLAM, and Scene Change Detection.
- Semantic SLAM: Participants use a robot to traverse around environments, building up an object-based semantic map from the robot’s RGBD sensor observations and odomtry measurements.
- Scene change detection (SCD): Participants use a robot to traverse through an environment scene, building up a semantic understanding of the scene. Then the robot is moved to a new start position in the same environment, but with different conditions. Along with a possible change from day to night, the new scene has a number objects added and / or removed. Participants must produce an object-based semantic map describing the changes between the two scenes.
Each task has two difficulty levels where the agent is supplied with either ground-truth or noisy pose data.
- March 15th – Challenge launch
- May – Submissions due
- June 19th – CVPR 2023 Embodied AI workshop
Dr David Hall (he/him)
Research Scientist
Data61 | CSIRO david.hall@csiro.au” target=”_blank” rel=”noreferrer”>
david.hall@csiro.au | 07 3327 4041
Turrbal Country
1 Technology Court, Pullenvale, QLD 4069, Australia
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