73 citations · 212 across the 46 of their papers we have counts for
9 papers · 1 filter
Any-scale Object Detection using Arbitrary-scaled Images
Kazutoshi Akita, Norimichi Ukita
This paper proposes any-scale object detection using arbitrary-scale super-resolution for continuously rescaling object images, while general multi-scale object detection uses disc…
Energy-Regularized Imitation Learning for Force- and Work-Aware Robotic Manipulation
Toshiki Otani, Hiromu Taketsugu, Norimichi Ukita
This paper studies energy-aware manipulation as a physically grounded learning problem. We define a joint-space mechanical-work proxy from joint torque and angular displacement, an…
PRISM: Predictive Representation of Interaction Style and Motion for Social Robot Navigation
Bo-Han Chen, Hiromu Taketsugu, Norimichi Ukita
Humans often observe others before interacting and adjust their behavior accordingly. Robot navigation in crowds, however, often represents pedestrians mainly by observed geometric…
A Plug-and-Play 2D Motion Interface for Real-World Motion Language Models
Kaname Yokoyama, Norimichi Ukita
Motion Language Models (MoLMs) typically understand human motions by tokenizing 3D motion and processing the resulting tokens using a language model. However, obtaining accurate 3D…
SAMIDARE: Advanced Tracking-by-Segmentation for Dense Scenarios
Shozaburo Hirano, Norimichi Ukita
Automated sports analysis demands robust multi-object tracking (MOT), yet segmentation-based methods often struggle with mask errors and ID switches in dense scenes. We propose SAM…
Group-DINOmics: Incorporating People Dynamics into DINO for Self-supervised Group Activity Feature Learning
Ryuki Tezuka, Chihiro Nakatani, Norimichi Ukita
This paper proposes Group Activity Feature (GAF) learning without group activity annotations. Unlike prior work, which uses low-level static local features to learn GAFs, we propos…
End-to-End Shared Attention Estimation via Group Detection with Feedback Refinement
Chihiro Nakatani, Norimichi Ukita, Jean-Marc Odobez
This paper proposes an end-to-end shared attention estimation method via group detection. Most previous methods estimate shared attention (SA) without detecting the actual group of…
Multi-Person Pose Estimation Evaluation Using Optimal Transportation and Improved Pose Matching
Takato Moriki, Hiromu Taketsugu, Norimichi Ukita
In Multi-Person Pose Estimation, many metrics place importance on ranking of pose detection confidence scores. Current metrics tend to disregard false-positive poses with low confi…
Human-in-the-loop Adaptation in Group Activity Feature Learning for Team Sports Video Retrieval
Chihiro Nakatani, Hiroaki Kawashima, Norimichi Ukita
This paper proposes human-in-the-loop adaptation for Group Activity Feature Learning (GAFL) without group activity annotations. This human-in-the-loop adaptation is employed in a g…