3 papers
cs.CV2025
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…
cs.RO2025
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…
cs.CV2025
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…