349 citations · 754 across the 23 of their papers we have counts for
23 papers
Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics
Kenta Oono, Nontawat Charoenphakdee, Kotatsu Bito +14
Virtual Human Generative Model (VHGM) is a generative model that approximates the joint probability over more than 2000 human healthcare-related attributes. This paper presents the…
Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network
Yuri Kinoshita, Kenta Oono, Kenji Fukumizu +2
Variational autoencoders (VAEs) are one of the deep generative models that have experienced enormous success over the past decades. However, in practice, they suffer from a problem…
F3 Hand: A Versatile Robot Hand Inspired by Human Thumb and Index Fingers
Naoki Fukaya, Avinash Ummadisingu, Guilherme Maeda +1
It is challenging to grasp numerous objects with varying sizes and shapes with a single robot hand. To address this, we propose a new robot hand called the 'F3 hand' inspired by th…
Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency
Aditya Ganeshan, Alexis Vallet, Yasunori Kudo +5
Deep learning models for semantic segmentation rely on expensive, large-scale, manually annotated datasets. Labelling is a tedious process that can take hours per image. Automatica…
A Scaling Law for Synthetic-to-Real Transfer: How Much Is Your Pre-training Effective?
Hiroaki Mikami, Kenji Fukumizu, Shogo Murai +5
Synthetic-to-real transfer learning is a framework in which a synthetically generated dataset is used to pre-train a model to improve its performance on real vision tasks. The most…
Uncertainty-Aware Self-Supervised Target-Mass Grasping of Granular Foods
Kuniyuki Takahashi, Wilson Ko, Avinash Ummadisingu +1
Food packing industry workers typically pick a target amount of food by hand from a food tray and place them in containers. Since menus are diverse and change frequently, robots mu…