17 papers
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…
CacheFlow: Fast Human Motion Prediction by Cached Normalizing Flow
Takahiro Maeda, Jinkun Cao, Norimichi Ukita +1
Many density estimation techniques for 3D human motion prediction require a significant amount of inference time, often exceeding the duration of the predicted time horizon. To add…