Robotic Interestingness via Human-Informed Few-Shot Object Detection
Seungchan Kim,Chen Wang,Bowen Li,Sebastian Scherer,Seungchan Kim,Chen Wang,Bowen Li,Sebastian Scherer
Interestingness recognition is crucial for decision making in autonomous exploration for mobile robots. Previous methods proposed an unsupervised online learning approach that can adapt to environments and detect interesting scenes quickly, but lack the ability to adapt to human-informed interesting objects. To solve this problem, we introduce a human-interactive framework, AirInteraction, that ca...
