95 citations · 273 across the 27 of their papers we have counts for
3 papers · 1 filter
PoseRN: A 2D pose refinement network for bias-free multi-view 3D human pose estimation
Akihiko Sayo, Diego Thomas, Hiroshi Kawasaki +2
We propose a new 2D pose refinement network that learns to predict the human bias in the estimated 2D pose. There are biases in 2D pose estimations that are due to differences betw…
Semantic constraints to represent common sense required in household actions for multi-modal Learning-from-observation robot
Katsushi Ikeuchi, Naoki Wake, Riku Arakawa +2
The paradigm of learning-from-observation (LfO) enables a robot to learn how to perform actions by observing human-demonstrated actions. Previous research in LfO have mainly focuse…
Text-driven object affordance for guiding grasp-type recognition in multimodal robot teaching
Naoki Wake, Daichi Saito, Kazuhiro Sasabuchi +2
This study investigates how text-driven object affordance, which provides prior knowledge about grasp types for each object, affects image-based grasp-type recognition in robot tea…