2 citations · 5 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
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…
Depth Estimation fusing Image and Radar Measurements with Uncertain Directions
Masaya Kotani, Takeru Oba, Norimichi Ukita
This paper proposes a depth estimation method using radar-image fusion by addressing the uncertain vertical directions of sparse radar measurements. In prior radar-image fusion wor…
R2-Diff: Denoising by diffusion as a refinement of retrieved motion for image-based motion prediction
Takeru Oba, Norimichi Ukita
Image-based motion prediction is one of the essential techniques for robot manipulation. Among the various prediction models, we focus on diffusion models because they have achieve…
Data-Driven Stochastic Motion Evaluation and Optimization with Image by Spatially-Aligned Temporal Encoding
Takeru Oba, Norimichi Ukita
This paper proposes a probabilistic motion prediction method for long motions. The motion is predicted so that it accomplishes a task from the initial state observed in the given i…
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
Goutam Bhat, Martin Danelljan, Radu Timofte +25
This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times hig…