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cs.CV2024
Fast LiDAR Data Generation with Rectified Flows
Kazuto Nakashima, Xiaowen Liu, Tomoya Miyawaki +2
Building LiDAR generative models holds promise as powerful data priors for restoration, scene manipulation, and scalable simulation in autonomous mobile robots. In recent years, ap…
cs.CV2024
Gait Sequence Upsampling using Diffusion Models for Single LiDAR Sensors
Jeongho Ahn, Kazuto Nakashima, Koki Yoshino +2
Recently, 3D LiDAR has emerged as a promising technique in the field of gait-based person identification, serving as an alternative to traditional RGB cameras, due to its robustnes…
cs.CV2024
Fast LiDAR Upsampling using Conditional Diffusion Models
Sander Elias Magnussen Helgesen, Kazuto Nakashima, Jim Tørresen +1
The search for refining 3D LiDAR data has attracted growing interest motivated by recent techniques such as supervised learning or generative model-based methods. Existing approach…