73 citations · 212 across the 46 of their papers we have counts for
10 papers · 1 filter
MMCM: Multimodality-aware Metric using Clustering-based Modes for Probabilistic Human Motion Prediction
Kyotaro Tokoro, Hiromu Taketsugu, Norimichi Ukita
This paper proposes a novel metric for Human Motion Prediction (HMP). Since a single past sequence can lead to multiple possible futures, a probabilistic HMP method predicts such m…
Efficient Cost-and-Quality Controllable Arbitrary-scale Super-resolution with Fourier Constraints
Kazutoshi Akita, Norimichi Ukita
Cost-and-Quality (CQ) controllability in arbitrary-scale super-resolution is crucial. Existing methods predict Fourier components one by one using a recurrent neural network. Howev…
Dynamic Group Detection using VLM-augmented Temporal Groupness Graph
Kaname Yokoyama, Chihiro Nakatani, Norimichi Ukita
This paper proposes dynamic human group detection in videos. For detecting complex groups, not only the local appearance features of in-group members but also the global context of…
Efficient Burst Super-Resolution with One-step Diffusion
Kento Kawai, Takeru Oba, Kyotaro Tokoro +2
While burst Low-Resolution (LR) images are useful for improving their Super Resolution (SR) image compared to a single LR image, prior burst SR methods are trained in a determinist…
MVA 2025 Small Multi-Object Tracking for Spotting Birds Challenge: Dataset, Methods, and Results
Yuki Kondo, Norimichi Ukita, Riku Kanayama +21
Small Multi-Object Tracking (SMOT) is particularly challenging when targets occupy only a few dozen pixels, rendering detection and appearance-based association unreliable. Buildin…
Selective Social-Interaction via Individual Importance for Fast Human Trajectory Prediction
Yota Urano, Hiromu Taketsugu, Norimichi Ukita
This paper presents an architecture for selecting important neighboring people to predict the primary person's trajectory. To achieve effective neighboring people selection, we pro…
Human Motion Prediction via Test-domain-aware Adaptation with Easily-available Human Motions Estimated from Videos
Katsuki Shimbo, Hiromu Taketsugu, Norimichi Ukita
In 3D Human Motion Prediction (HMP), conventional methods train HMP models with expensive motion capture data. However, the data collection cost of such motion capture data limits…
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…
Robot Motion Planning using One-Step Diffusion with Noise-Optimized Approximate Motions
Tomoharu Aizu, Takeru Oba, Yuki Kondo +1
This paper proposes an image-based robot motion planning method using a one-step diffusion model. While the diffusion model allows for high-quality motion generation, its computati…
Physical Plausibility-aware Trajectory Prediction via Locomotion Embodiment
Hiromu Taketsugu, Takeru Oba, Takahiro Maeda +2
Humans can predict future human trajectories even from momentary observations by using human pose-related cues. However, previous Human Trajectory Prediction (HTP) methods leverage…